Headshots of female Amazon scientists participating in the Grace Hopper Conference.
Amazon scientists (from top left) Kristine Brown, Laura De Lorenzo, Yang Liu, Hannah Marlowe, Nina Mishra, Candace Thille, and Chao Wang provide their perspectives on what it will take to attract more women to pursue STEM careers.
Credit: Stacy Reilly

Seeds of inspiration

Given the recent death of US Supreme Court Justice Ruth Bader Ginsburg, and with the Grace Hopper Celebration taking place this week, we asked Amazon women scientists what it will take to attract more women to pursue STEM careers.

The AnitaB.org Grace Hopper Celebration, an event honoring Grace Hopper’s legacy by inspiring future generations of women to pursue careers in technology, takes place this week, as it has every year since 1994. Amazon is a Diamond sponsor of this year’s event.

Unlike previous years, though, this year’s celebration, which AnitaB.org produces in partnership with the Association for Computing Machinery (ACM), will be held virtually given restrictions related to COVID-19.  What hasn’t changed is the vision of AnitaB.org: a future “where the people who imagine and build technology mirror the people and societies for whom they build it.”

Based on the latest statistics from the National Center for Women & Information Technology, that future is still on the horizon. While 57 percent of US professional jobs were held by women in 2019, just 26% of professional computing jobs were occupied by women. Among the 26% of women occupying professional computing jobs, 7% were Asian women, 3% Black women, and 2% Hispanic women.

Elizabeth Nieto, Amazon’s head of global diversity and inclusion, says the company’s vision is to create a culture where the best builders, including women from all backgrounds, want to work and stay at Amazon “because they are drawn to our mission, our culture, and our leaders. We are focused on being globally inclusive and creating a culture at Amazon where everyone can reach their full potential.”

At last year’s event, Brenda Darden Wilkerson, president and CEO of AnitaB.org, told nearly 25,000 attendees, “I want our daughters to say, ‘I heard back in the day there was this problem that there weren’t enough women in tech.  What was that like?’”

In advance of this week's conference, Amazon Science asked some of the company’s women scientists when they think the industry will reach that goal, what it will take to get there, and who or what most inspired them to pursue their science careers.  Below are their responses.

Kristine Brown is a principal economist within Amazon’s human resources organization. She obtained her PhD in economics from the University of California, Berkeley.

Kristine Brown
Kristine Brown

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

At Amazon, I learned the importance of continuous inspection to identify opportunities for improvement, and to adapt to a shifting environment. I think the same applies here; the task of deliberately creating opportunities for others, and removing barriers to shape a more equitable and inclusive workplace will evolve over time, but it doesn’t have an end date.

Q. What will it take to get there?

The demand for science and tech talent is increasing in the traditional technology sector and in other industries that are leveraging new technologies and data to provide better services and products. The door is wide open, but you can’t walk in if you don’t know it exists, or how to get there. For me, early exposure and encouragement to explore science and math were critical. I discovered a passion for physics and that interest pushed me to develop my math and science skills. I was lucky to have this opportunity. Casting a wider net to provide early, low stakes opportunities to engage in science and tech activities, develop STEM skills, and learn about the diversity of work in this space, will help demystify the technology industry. It will also allow kids and young adults to learn whether it matches their interests and whether they have a knack for it.

Q. Who or what inspired you most to pursue your STEM career?

My fascination with the natural world was fueled by observing wildlife, peering through an observatory telescope at distant planets, and nature magazines with beautiful photos. The mind-bending questions of space and time were especially irresistible; I wanted the answers to the universe, and physics and math were the key to finding them. Later, as I became interested in understanding human behavior (which I’d argue is no less mysterious) and how government policies could improve lives, I found economics came with a familiar toolkit of mathematical modeling and scientific testing to answer these questions. I saw a career in economics as an opportunity to leverage my strengths to drive positive change.

Laura De Lorenzo is a quantum computing research scientist within the Amazon Web Services organization. She earned her PhD in applied physics from the California Institute of Technology (CalTech).

Laura De Lorenzo
Laura De Lorenzo

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

To be honest, I'm so uncertain as to be unwilling to hazard a guess, but I do think it is a long way off. In some STEM fields, such as medicine, the gender gap has nearly, or completely, closed within the past 50 years. In other fields, the percentage of women (measured by employment or educational degree) remains far below 50% and doesn't appear to be changing significantly year over year. The amount of progress in some fields is encouraging, but it's difficult to understand why fields like physics and computer science lag behind.  

Q. What will it take to get there?

This issue is clearly challenging and multi-faceted, so I cannot offer a single simple solution. However, I think one important aspect is a focus on young women, in the middle school to high school age group. For example, women are already underrepresented in the high school AP physics examinations. By the time students reach the undergraduate level, only about 20% of physics majors are female. I think it is essential to understand why young women make these choices. Is it a lack of role models, or self-doubt about their ability to perform well in science, or peer pressure, or something else entirely?  In the meantime, I think it is important to offer encouragement and support to young students because once women drop out of the STEM fields, it is more difficult for them to return at a later age.

Q. Who or what inspired you most to pursue your STEM career?

From a young age, my parents were always supportive of my interests in science and math, and of my career in general. My mother went to medical school in the late ‘70s, when women represented only about 20% of medical students in the US.  I always saw her as strong, hard-working, and independent, and she was a great example for me to follow. Both of my parents had high expectations for me and would never allow me to perform at less than my best. I definitely owe the largest debt of gratitude to them. However, programs such as Science Olympiad and the Pennsylvania Governor's School for Science (a five-week program for rising high school seniors), also helped me by introducing me to a peer group with similar interests, and to a larger group of role models and mentors who could help me navigate the next step.

Yang Liu is a principal scientist within the Alexa AI organization. She earned her PhD in electrical and computer engineering from Purdue University.

Yang Liu
Yang Liu

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

Maybe in another generation. My daughter is in first grade now. I’m hopeful we can reach that day when she finishes high school, and is choosing a college major or planning a career in STEM or the technology industry.

Q. What will it take to get there?

It will require effort from everyone in society, including educators, students, parents, and policy makers. Starting from kindergarten through high school, young girls and women need support and encouragement from parents and teachers to realize their potential and get excited by STEM careers; educators need to nurture girls’ interest in STEM and create an environment to help them do well in these subjects; and policy makers need to provide appropriate and adequate resources for teachers and students. As Hillary Clinton has written and said, it will take a village for society to address existing biases and prejudices. But with everyone’s effort, I’m confident we can get there by the time my daughter is entering the workforce.

Q. Who or what most inspired you to pursue your STEM career?

Mostly just people around me — my family, teachers from elementary schools all the way up to universities, and an overall supportive environment, including friends and peers. I grew up in China. My mom was a math teacher, and I did well in math starting in elementary school. All I got from everyone around me was support, respect, and encouragement to continue to excel in this subject. I never encountered an attitude like “girls are not good at math (or other science subjects) or don’t need to do well in math”. I made many friends (girls and boys) in schools, and was never left out because I did better than others in science. Reflecting on this, there’s no doubt I benefited from that supportive environment, leading to my future career in STEM. I don’t know for sure if there is a difference between China and US; I don’t have enough sample to draw a conclusion. I’m not even sure if there’s been a generational change within China. What I can say is that I would encourage girls and young women to pursue STEM careers.  The subjects themselves are fascinating. Right now I’m working within the Alexa organization on making computers and other devices “intelligent” by recognizing speech and understanding human language. The work is challenging, interesting, and it’s great to see how Alexa can have a positive impact on the lives of our customers. 

Hannah Marlowe is a senior data scientist within the AWS Worldwide Public Sector Professional Services Data and Machine Learning team. She earned her PhD in physics from the University of Iowa, specializing in the study of astronomical X-ray sources and space-borne instrumentation development.

Hannah Marlowe
Hannah Marlowe

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

The university building where I completed my PhD was an interesting time-capsule to observe some of the progress of women in physics and astronomy. The eight-level physics building, built in the ‘60s, originally featured only men’s restrooms apart from one. The lone women’s restroom was located across the hall from the administration office and included an attached kitchen (still there today), presumably so that secretaries working in the office could prepare meals during the work day. In years since, they have thankfully adjusted the restroom situation, but the basement where my team’s lab was located still only had a men’s room and it was always an interesting reminder of that past.

Today, the thought of designing a building with facilities only for men (much less a public university building) seems completely ridiculous, but it wasn’t so long ago that it apparently made practical sense. We are standing on the shoulders of giants like Ruth Bader Ginsburg and other advocates of gender equality who paved the way for the participation of women in traditionally male-dominated fields and shifted public perception of what women can and should do. It is my hope that we continue to build on the work they championed, but it will take a concerted effort. I don’t have a good answer for when I think we will get to the point that gender disparity in STEM fields is a distant memory. However, I have seen positive changes and witnessed shifts over my own career (not limited to restroom design choices) that make me optimistic that we can get there eventually.

Q. What will it take to get there?

I don’t believe there is any one right answer, but one of the most important things is making it clear to young girls and women that they belong and add value in STEM. I think people tend to gravitate to careers and roles that they have exposure to, and where they see role models that look like themselves. The other piece is not just encouraging girls and women to explore STEM, but expecting it and treating it like a normal career path versus an exceptional one. That is not to say we should be pushing girls to pursue something they aren’t interested in, but I hope that we get to a point where girls pursuing STEM seems completely boring and commonplace. That gets easier as more women enter STEM fields, and I think there is probably a tipping point where women and girls just naturally begin to gravitate in larger numbers to these fields. As a practical matter, we should also be equipping girls with all of the skills and tools that will make them successful in these fields from a young age. Anyone who isn’t exposed to math and science early is going to have to play catch-up later on, and may question their own abilities when they compare themselves to peers who have been in advanced math and science tracks throughout grade school.

Q. Who or what most inspired you to pursue your STEM career?

I feel extremely fortunate that I have mainly been able to follow my interests and what I found to be fun and personally challenging throughout school and my career so far. I also had many great influences and mentors in my life that helped me along my path. From an early age my father used to point out constellations in the sky and took my sister and me to observe comets and space shuttle launches. Once I got to high school, I had a wonderful retired NASA engineer as a physics teacher who introduced me to physics and to Carl Sagan and helped us start the first astronomy club at our school. For my undergraduate education, I chose a small women’s liberal arts college, Agnes Scott College, that had its own observatory and offered an astrophysics degree. At Agnes, I had excellent professors and the unique experience of having all of my STEM peers be women. I think that experience especially helped inoculate me for the future where I’ve more often found myself the only women in large lab groups, collaborations, and professional teams.

The last thing I would like to mention here, because I think it is really important and something I have often struggled with, is the issue of self-doubt. Self-doubt and imposter syndrome are definitely not limited to women in STEM fields, but I think being the only one around who looks like you can contribute to those feelings, and can push people away who have wonderful things to add to these fields. I have so often questioned myself and my worthiness, intelligence, and value (did I really earn that award/fellowship/job offer or was I selected just because I am a women/was in the right place at the right time/completely by mistake?). It was really important for me to know that I was not alone in doubting myself and my capabilities and I am grateful to colleagues and mentors, men and women alike, who shared their own experiences with self-doubt and imposter syndrome along the way. I’ll always remember my wonderful, brilliant, and inspiring undergraduate professor telling me about her own struggles in graduate school, and that one of the reasons she became a professor was to show us that “if she could do it, any of us could.”

Nina Mishra is a principal scientist Amazon’s Health and Wellness organization. She earned her PhD in computer science from the University of Illinois at Urbana-Champaign.

Nina Mishra
Nina Mishra

Q. When do you think we’ll reach that day that Brenda Wilkerson talked about last year?

While computer science has had a gender gap since its inception, I was convinced early on that a trifling matter like gender difference would self-correct. I was wrong. According to a 2019 Taulbee survey, 80% of PhDs are awarded to men and 20% to women. Back in 2001, the split was 78%/22% -- essentially unchanged after 18 years. The problem is not likely to improve in the next five years since the 80/20 gap persists in 2019 at the computer science bachelor’s degree level. Beyond gender gap, there is a gaping wide race gap. In 2019, less than 1% of PhDs were awarded to Black or African-American students; in 2001 this number was 1.3% -- again, essentially the same.  This gap persists early in the education pipeline.  For example, while Atlanta’s population is more than 50% black, only 3 Black students are enrolled in advanced placement computer science courses in local public high schools -- that is 3 out of 528,000! Narrowing this gap is critical for the technology industry. Companies do not want the lack of diversity in their workforce to perpetuate into their products. When will we reach that day? When we change the computer-science culture to welcome and embrace differences. 

My hope, adapting the words of others, is that the arc of social justice is long, but bends towards equality.
Nina Mishra

Q. What will it take to get there?

We cannot reach parity until we overturn the presumption that women hold different roles than men. Until we eliminate the idea that there are ‘girls’ disciplines’ and ‘boys’ disciplines’, and slights such as asking a woman in a meeting if she’s a secretary, or if she can get water for the meeting, it will be difficult to make progress.  Derogatory comments like these contribute to the ‘million cuts’ that women experience and can ultimately lead people to pursue careers where they are more wanted. I’m surprised that people are still hung up on these role associations, but the concern is real and people like Ruth Bader Ginsberg fought their entire career to overturn them. My hope, adapting the words of others, is that the arc of social justice is long, but bends towards equality.

Beyond reaching parity, underrepresented groups need to be seen and more prominently heard. All people have amazing ideas, but I have repeatedly seen ideas from underrepresented groups diminished and even discarded. When such ideas later resurface with the ownership transferred to someone in an overrepresented group, the process is demoralizing and influences people to find alternate careers. These injustices need to be reported and escalated to higher levels. The problem can only be fixed if we have an active dialogue starting from a young age.

Accessibility of resources is a consideration in some parts of the country. There are still households where students do not have a computer and others where a single computer is shared among many family members. There are households that do not have internet access. And, there are parts of the country where computer science classes and teachers aren’t available to students. People cannot choose a computer science career if they are missing these simple, starter ingredients.

Outreach is another area where we can do more. Students may wonder, `What will I do if I have a career in STEM?’. Everyone knows what a medical degree or a law degree leads to career-wise, but what does a computer science degree lead to? The common misperception is of macho geeks cranking out tons of code. For me, it is about finding ways to use data collected about some people to help millions more. It is about the amazing predictions that machine learning can make. The way that smartwatches can detect heart arrhythmias and search engines connect people to information is rooted in data and machine learning. Writing code is a means to that end. Novel and crazy ideas are what push the field forward. A more concerted effort is needed to communicate this to young students.

Q. Who or what most inspired you to pursue your STEM career?

My mother played a huge role early in life. She has a gift for explaining mathematical concepts. She taught math at a community college and also a prison. Later on, my high school math teacher played a large role. She forced students to walk to the board and write/explain their solutions. It was an early peek into the clarity one achieves by teaching their solution to others. Both taught me the precision and beauty of math. Both insisted on exacting standards for the highest quality of work. My father taught me to be bold. He has a PhD in inorganic chemistry and emphasized scientific innovation. To this day, he shares articles with the latest and greatest scientific findings, always pushing me to aim higher.

Candace Thille is director of learning science within Amazon’s Global Learning and Development organization. She obtained her master’s degree in computer science from Carnegie Mellon University and earned her PhD in education from the University of Pennsylvania.

Candace Thille
Candace Thille

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

I am going to change the question to respond to what I wish Brenda Darden Wilkerson had said: “I want our sons to say ‘I heard back in the day there was this problem that there weren’t enough women in tech. What was that like?” I do not mean to imply that the quote needs to be changed because the problem is only important if it is acknowledged by our sons, but rather that the problem will only be corrected when the problem, and the responsibility for correcting it, is owned by our sons too, not just our daughters.  When will we reach that day?  When gender is no longer seen as a feature of an individual that is relevant for encouraging, allocating, or selecting roles and responsibilities.

Q. What will it take to get there? 

First, an acknowledgement that the current systems and structures in STEM fields are grounded in the idea that gender and race are features of an individual that are relevant for encouraging, allocating, or selecting roles and responsibilities. Second, a commitment to ongoing inspection of those systems and structures for biases in order to change them. People would sometimes ask Ruth Bader Ginsberg “When will there be enough women on the court” and she would reply, “When there are nine”.  She would say then that “People are shocked, but there’d been nine men, and nobody’s ever raised a question about that”.  

Q. Who or what most inspired you to pursue your STEM career?

I have always been fascinated with how things work, both for the joy of understanding and to figure out how to make things work better. I have been awed by the discoveries that come from good research, and from the positive impact of using the results from research to make the world better. Both as an academic researcher and as a research scientist at Amazon, I situate my work in Pasteur's quadrant and work on projects that seek fundamental understanding of scientific problems, while also having immediate use for society.

Chao Wang is a senior applied science manager within the Alexa organization. She earned her PhD in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT).

Chao Wang
Chao Wang

Q. When do you think we'll reach that day that Brenda Wilkerson talked about last year?

I’m reminded of the Bill Gates quote, “We always overestimate the change that will occur in the next two years, and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.” I’d like to think we could reach that state within the next 10 years, but it will probably take another generation of change. So I think closer to 2050.

Q. What will it take to get there?

I’ll share a very different perspective. I grew up in China and the education system back then made everyone decide their major in sophomore year of high school. That system channeled students to different college entrance exams depending on the choice (so your career paths are largely determined very early on). It was a 5:2 split ratio for STEM and non-STEM (probably matching the college admission ratio), and naturally only students who were really interested in a non-STEM career path self-selected into that track. The majority chose STEM. At the time, I did notice that more female students chose the non-STEM track, but plenty of us ended up in the STEM track, too (strength in numbers). I have observed that in the US, if you are ambivalent about STEM, then the gender stereotype works against young women pursuing STEM careers. I contrast that with the early days of computing in the US, when computer programmer was considered a female job, and you had a lot of female programmers in an otherwise male dominant technology industry and computing pioneers like Dr. Grace Hopper. It all changed (for the worse) within a generation, and we can change it back with the right societal mental shift.

Q. Who or what most inspired you to pursue your STEM career?

Growing up in China I never felt that STEM was somehow an unusual choice for a young woman. Math and physics were always my favorite subjects, and no one ever discouraged me from pursuing those interests. I enjoyed the problem solving of math and physics much more than courses requiring writing or memorization. I opted for the STEM track in high school and was admitted into a top engineering school in China for my undergraduate studies. My career path was more or less decided from that point in time.


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Job summaryAmazon Advertising seeks an Economist to help develop an automated financial forecasting system for our DSP advertising business, and help model key relationships that drive advertiser value and impact our financial performance. We are looking for a motivated candidate who has operated successfully in a fast-paced, global, results-oriented environment and has the ability to influence the decisions of senior business leaders through effective verbal and written communication, logical reasoning, and the presentation of analyses. The successful candidate will collaborate closely with business teams to help execute and shape our product and financial strategy.If you enjoy using Econometric methods to shape strategy and build new initiatives from concept to full-scale operations this will be a good match. We are looking for a highly motivated individual to develop deep industry understanding, create new models gaining insight into advertising performance, analyze monetization strategies to maximize revenue, and provide guidance for feature roadmap prioritization and decision-making. This position will collaborate with business leaders on a daily basis and will be contributing to overall financial modeling and analysis during our operating cycle plans, periodic forecast updates, requirements planning, business reviews, and providing business insights into key initiatives.The successful candidate will be a self-starter who is comfortable with ambiguity; dives deep into data to find key relationships, creates models to better understand and forecast processes, is detail oriented and has the ability to work well with cross-functional teams including product development, science, sales, other finance teams, and senior leaders.About the teamThis role is open to the following locations: Los Angeles, Seattle, San Francisco, Washington DC/Arlington, VA.
DE, BE, Berlin
Amazon Simple Storage Service (S3) is storage for the Internet. Through the use of pioneering techniques in storage & computing, customers can reliably store their data on Amazon’s proven computing infrastructure to achieve virtually limitless storage capacity at minimal cost. Amazon S3 provides a simple web services interface that enables customers to store and retrieve any amount of data from anywhere in the world. We build and run the largest commercial storage system in the world with trillions of objects and regularly serving millions of requests per second.We’re looking for an Applied Scientist to join the team in Berlin, Germany to help us build a next generation product. The ideal candidate is excited about the incredible opportunity that cloud computing represents, and is passionate about delivering quality services in a hyper-growth environment where priorities can shift fast. You’ll make our customers’ lives better through the features and service improvements that you own and deliver, and will work with other leaders in the team to guide both the success of the Berlin office and S3 as a whole. As part of our team, you’ll be able to bring innovation and execute on new ideas that will raise the bar on what our customers can achieve with S3. You will be working with customers to design and build the technology that powers applications that you love like Airbnb, Netflix, Uber, and many more.If this sounds like you, come join us and help AWS continue to write the cloud computing story for the industry.Work-life Balance - Our team works together to provide work/life balance for all team members. We recognise that the circumstances of our team members vary, and we balance work across the team so we’re all able to maintain standards on behalf of our customers, while at the same time allowing for rich and happy personal lives.Mentorship & Career Growth - We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level, etc. We can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so we are always learning from one another, and we celebrate and support the career progression of our team members.Inclusive Team Culture - We have a diverse team and drive towards an inclusive culture and work environment. Our team is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Our team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Amazon Women and Engineering, and LGBTQ+Ownership is central to everything we deliver at Amazon. You will own the entire lifecycle of your work from design to implementation, testing, and operations. We strive to build a collaborative work environment that lets you both broaden your impact and grow with the support of mentors and senior engineers on the team.Creating a reliable, scalable, and flexible web service requires a deep understanding of the fundamentals of Computer Science and practical experience building large-scale distributed systems. You should be somebody who enjoys working on solving complex problems, is customer-centric, and feels strongly not only about applied science to innovate on behalf of our customers. Join us and help solve a challenging set of problems in a space packed full of opportunities.Key responsibilities include:· Researching, designing and developing innovative solutions to complex problems in storage systems such as S3· Defining and executing on a research roadmap for S3. You’ll know and talk with your stakeholders on a regular basis, as well as using data and metrics to understand how your service is used, and build and deliver on a roadmap that delights our customers.· Having fun working on ground breaking technology with people just as passionate about their work as you!We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.The Berlin S3 team is fun, ambitious, growing, and a great place to be able to have impact. If you’re a passionate software engineering leader excited about solving difficult problems at the challenging scale of AWS, we’d love to hear from you.A day in the lifeAbout the hiring groupJob responsibilities
US, MA, Boston
Job summaryAmazon Detective team is looking for a scientist with a strong background in machine learning and distributed computing to join our group that spearheads the development of next-generation graph-based analytics and AI systems for security investigations.Amazon Detective is one of the AWS External Security Services. Amazon Detective makes it easy to analyze, investigate, and quickly identify the root cause of potential security issues or suspicious activities.We are a team of scientists with varied research backgrounds and experience who worked on problems ranging from discovery of gravitational waves, to quantum computing, to robotics and more. We embrace diversity of thoughts and encourage original ideas. We emphasize collaborative work culture and support professional growth. Our team is tackling some of the most challenging problems at the intersection of cyber-security, big data, and machine learning. If you are motivated to work on advancing technology and making a positive societal impact at the unprecedented scale, then this is the team for you.The AWS External Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. Our scientists work hands-on in close collaboration with security technicians, engineers, and product managers. We are customer-obsessed, and focus on research that brings value to our customers.Key Responsibilities:· Design, prototype, and validate graph models for security data, using both quantitative and business judgment· Develop new data-analysis algorithms and tools· Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex production services.· Report results in a scientifically rigorous way· Collaborate with security engineers and other scientists at Amazon on the state-of-the-art research projectsHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, MA, North Reading
The Research and Advanced Development team at Amazon Robotics is seeking innovative hands-on scientists to work on cutting edge algorithms to power automation in Amazon’s order fulfillment and transportation network. Our multi-disciplinary team includes scientists with backgrounds in AI planning and scheduling, robotic grasping and manipulation, machine learning, and operations research. We work on problems such as:- Dynamic allocation and scheduling of tasks to thousands of robots- Learning how to manipulate all the products that Amazon sells- Planning and coordinating the paths of thousands of robots- Co-design of robotic logistics processes and the algorithms to optimize themThe ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses!Inclusive Team CultureHere at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 87,000 employees across hundreds of chapters around the world. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust.FlexibilityIt isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthWe care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.
US, CA, San Diego
The Amazon Private Brands Intelligence team applies Machine Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We develop statistical models and algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Scientists, and Engineers building Day One solutions using cutting-edge technology to solve some of the toughest business problems for Amazon Private Brands (APB).You will work with business leaders, scientists, economists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable ML models. You will invent and implement scalable ML, RL, and econometric models while also building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists, economists, and engineers. We are particularly interested in candidates with experience building predictive models and working with distributed systems.As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.To learn more about Amazon science, please visit https://www.amazon.scienceAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!As a Data Scientist on this team, you will:· Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.· Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data· Apply statistical and machine learning knowledge to specific business problems and data.· Build decision-making models and propose solution for the business problem you define.· Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.· Analyze historical data to identify trends and support optimal decision making.· Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.· Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.· Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raE
US, CA, San Diego
Job summaryAmazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.Please visit https://www.amazon.science for more information.Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud?Do you want to build advanced algorithmic systems that help manage safety of millions of transactions every day?Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems?Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention Machine Learning group.Major responsibilities· Use statistical and machine learning techniques to create scalable risk management systems· Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends· Design, development and evaluation of highly innovative models for risk management· Working closely with software engineering teams to drive real-time model implementations and new feature creations· Working closely with operations staff to optimize risk management operations,· Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· Tracking general business activity and providing clear, compelling management reporting on a regular basis· Research and implement novel machine learning and statistical approaches
US, VA, Arlington
Job summaryThe AWS Infrastructure Planning group is responsible for planning and coordinating a complex, multi-tier supply chain that delivers capacity for all AWS services. This includes data center setup, equipment purchase, installation and operation of servers with power and cooling, inventory management and other such decisions. We're building a new suite of tools to automate all AWS supply chain planning, with a broad charter that involves inventory optimization, placement, vendor allocation, transition management, lead time predictions, and more. We are responsible for ensuring that the AWS cloud remains elastic for its customers by taking care of all of the back-end complexity, enabling our infrastructure to stay ahead of our rapid growth.As an Applied Scientist you will use your experience to develop new strategies to improve the performance of AWS Infrastructure’s planning systems and networks. Working closely with fellow applied scientists and product managers, you will use your experience in modeling, optimization, and simulation to design novel algorithms and models of new policies, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our supply chain.We are looking for experience in network and combinatorial optimization, algorithms, data structures, statistics, and/or machine learning. You will have an opportunity to work on large mathematical problems, with large elements of unpredictability. You will write and solve linear and mixed-integer problems to find optimal solutions to build decisions given capacity constraints and the demand distributions. You will also drive process changes that comes with automation and smarter optimization.Key job responsibilities· Design and develop mathematical, simulation and optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of inventory management, network flow, supply chain optimization, demand planning.· Apply theories of mathematical optimization, including linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.· Prototype these models by using modeling languages such as R, MATLAB, Mosel or in software languages such as Python.· Create, enhance, and maintain technical documentation, and present to other Scientists, Product, and Engineering teams.· Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans· Influence organization's long term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists.About the teamThe AWS Infrastructure Supply Chain Technology Applied Research team drives technological advances and develops machine learning, optimization and simulation products to address complex challenges in the AWS Infrastructure supply chain.We sit at the intersection of science and engineering, and innovate on behalf of customers to solve ambiguous problems that haven’t quite been fully articulated or even anticipated.
US, NY, New York
Exciting new opportunity as the founding team member for Sponsored Products beyond the retail store!If you are looking to make an impact, this is the team for you. You will not only have the satisfaction of seeing your work directly on the Amazon website and beyond where it will be viewed by tens of millions of customers and drive quantifiable revenue impact, with the opportunity to help shape our engineering and product roadmaps. We are not bound by legacy systems and have a broad mandate to experiment, which gives us great flexibility as we design and develop our services. You will have an opportunity to contribute across the full stack and even dabble in some novel Machine Learning opportunities. Most importantly, you will have an opportunity to grow and broaden your technical skills as you work in an environment that thrives on creativity, experimentation, and product innovation.Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!As a Senior Data Scientist on this team you will:· Lead Data Science solutions from beginning to end.· Deliver with independence on challenging large-scale problems with complexity and ambiguity.· Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data.· Build Machine Learning and statistical models to solve specific business problems.· Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.· Analyze historical data to identify trends and support optimal decision making.· Apply statistical and machine learning knowledge to specific business problems and data.· Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.· Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.· Build decision-making models and propose effective solutions for the business problems you define.· Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video ~ https://youtu.be/zD_6Lzw8raE
US, WA, Seattle
Job summaryAre you passionate to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions to help Selling Partners and Customers on Amazon? Want to work on the business that is the lifeblood of Amazon? Selling on Amazon is one of the fastest growing businesses at Amazon.com and empowers millions of entrepreneurs worldwide. Our team will invent and innovate across technology, processes and people to grow the program, improve engagement and satisfaction and enable scalable solutions.We are looking for an Economist to lead us to identify data-driven insight and opportunities to improve our seller recruitment strategy and drive new seller success. As a successful economist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user of econometric models and advanced quantitative techniques for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with economists and scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).What you'll do:· Provide data-driven guidance and recommendations on strategic questions posed by the NSS leadership.· Design and analysis of account coverage experiments and define and analyze success metrics across sales team optimization, marketing and new seller education and recommendation programs.. Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results.· Provide technical and scientific guidance to your team members, both junior and senior.· Communicate effectively with senior management as well as with colleagues from science, engineering, and business backgrounds.
GB, London
Are you interested in delighting Alexa customers around the world? We have a unique position in the Alexa AI Knowledge team to solve interesting problems related to speech recognition and question-answering, across the languages we support.Our challenge is to ensure Alexa answers every question in any language, on any topic, at any time. "Who won the football match?", "How long till Diwali?", "How old is Dresden Cathedral?" We aim to answer these questions the first time they are asked in a way that’s natural, engaging and fun.We’re looking for an Applied Science Manager to lead a cross-functional team in developing novel techniques (e.g. deep neural network architectures) and deploying them to production toward our end goal of reducing the friction customers feel when Alexa doesn’t understand a user’s spoken question or when it requires repeating or rephrasing to get an answer. The ideal candidate has the requisite background and experience in building high-performing, collaborative teams. This person is versed in cutting-edge research and has an eye for hiring and developing talent.We have an opportunity to make a large and long-lasting impact for our customers. This job will test your skills across the board. Interesting problems? Check. Collaborative, curious and caring team? Check. Opportunities to invent at scale? Check. Opportunities to grow our exceptional talent? Check.Our challenges are big and the pace is fast. We provide a high-energy, empathetic, and supportive environment. Come join us if you like to put the customer at the center, invent, and think long-term. At Amazon, it's still Day 1.This position is based in London.
US, NY, New York City
Job summaryIn the Amazon Product Knowledge Team, we are building comprehensive schematic and semantic constructs to understand customer intent, in order to provide a delightful experience that feels targeted to their shopping mission. It expands beyond factual product characteristics (e.g. resolution of a TV) to additional dimensions used in customer shopping missions: what the product is used for (e.g. baby-proofing), where the product is used (e.g. kitchen), who uses the product (e.g. teenager), when the product is used (e.g. thanksgiving), and opinions about the product (e.g. cute t-shirt). We build scalable solutions that are partially or entirely powered by AI and ML to discover Product Knowledge by mining seller signals and customer engagements (e.g. search queries, customer reviews, web pages, etc).We have multiple positions for applied scientists who are excited to work on big data challenges including; web scale data integration, natural language processing, discovery of new relationships along with their semantics, knowledge inferencing and enhancement, knowledge embedding, entity recognition, and improving data quality to support strategic and tactical decision-making in building Product Knowledge.We are looking for applied scientists with experience in building practical solutions who can work closely with software engineers to ship and automate solutions in production. Our applied scientists also collaborate and partner with teams across Amazon to understand and reflect on how to create benefit for every customer.
US, CA, Pasadena
Job summaryJoin us in a historic endeavor to make Computer Vision accessible to the world with breakthrough research! The AWS AI Labs Computer Vision team has a world-leading team of researchers and academics. We develop the algorithms and models that power AWS computer vision services, such as Amazon Rekognition, Amazon Textract, and Amazon Lookout for Vision, and we conduct and publish long-term research in broad areas of computer vision.We are looking for a senior applied science manager to join us and make the AI revolution happen through innovative research inspired by customer needs. As a Senior Applied Science Manager, you will identify research directions, create and execute roadmaps for forward-looking research and communicate them to senior leadership. You will partner with product teams to define what’s feasible while pushing the envelope on what’s possible. You will work closely with engineering teams to bring research to production. You will manage and lead multiple teams of talented scientists and science leaders, and grow the team by attracting the best scientists in computer vision and deep learning. You are expected to develop innovative solutions to hard problems, and lead your teams to publish your research results at peer reviewed conferences and workshops.AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give scientists endless opportunities to see their research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world.Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods, multimodal learning, semi-automated data annotation, large scale image and video recognition, face detection and recognition, document OCR and scene text recognition, document understanding, and geometric computer vision.We are currently located in the US (Seattle, Pasadena, and Bay Area) and Israel (Haifa and Tel Aviv). We are open to candidates interested in working either virtually or remotely from another Amazon location. Additional locations include San Diego and New York City.About Us Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, TN, Nashville
Job summaryAmazon’s vision is to be Earth’s safest place to work. As part of the vision to be Earth’s safest place to work, we are undertaking a multi-year initiative to reduce musculoskeletal disorders in our operations by 40% by 2025. The practice of Human Factors/Ergonomics within our company is key to achieving this goal. We are seeking a Human Factors and Ergonomics (HFE) Research Science Leader to spearhead applied research projects using advanced technologies that will translate to real world solutions and define industry leading best practices. We are looking for an exceptional researcher, someone that is excited to work on complex challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will define human factor /ergonomic thresholds resulting in design and implementation of safe and efficient workspaces and processes for our associates, and beyond.Key job responsibilitiesYour responsibilities include:1. Identifying cross organizational challenges for which a rigorous research approach is necessary to invent and simplify.2. Working with senior leadership to determine research strategy and direction.3. Initiating, leading, and managing complex laboratory and field-studies using state-of-the-art methodologies, including.a. Managing and mentoring of assigned project personnel.b. Developing of custom data acquisition and analysis software solutions.c. Seeding the translation of research findings to cross functional stakeholders in design, engineering, safety, and operational groups.4. Develop programs to ensure senior executives and decision makers in the organization are up to speed on important trends, tools, and technologies and how these may positively affect our operations.5. Expand our global focus by supporting distributed teams and building a global research presence.6. Enable learning and application of research skills by designers, engineers, and operational personnel by building programs, platforms, and toolkits that empower them to effectively conduct quality research.7. Travel to our various sites globally to lead and perform studies and gain in-depth operational feedback, up to 40% of your time.
US, WA, Virtual Location - Washington
Job summaryAmazon’s Employee Relations (ER) team is looking for a Data Scientist (DS) with a demonstrated passion for building innovative new analytics, models, tools and processes for our Employees and Leaders. Are you looking for an opportunity to build in a completely new space that will stretch you and force you to demonstrate your mastery of data science, data analytics, problem solving and enterprise wide deployments? This DS will lead new pioneering ideas from concept to reality and in this role—new bold ideas are always welcome. This DS will obsess over the Amazon employee experience and the employee voice across the organization. This DS will directly apply their knowledge to dig deep and help Amazon leaders gain actionable insights. Finding, prioritizing and resolving employee experience defects will be the mission every day. Thus, the challenge of this role is that it is never complete; we will always strive to push Amazon to be the Earth’s best employer.The Data Scientist will play a critical role in advancing our mission. You will join a tight-knit team of ER professionals, including HR, operational, program, product, tech and legal leaders. You will be supporting Amazon's World Wide Corporate, Consumer and Operations (WWCC & Ops) portfolio, and have direct impact on the daily work of over 1.3M+ Amazonians.Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, dashboarding and predictive machine learning tools. We’re looking for an enthusiastic technical expert and storyteller to explore the world of Amazon data to generate insights—connecting employee experiences to decision makers in a compelling way backed by data. Your focus will cover all aspects of how we learn more about our employees, uncover problems that need to be solved, and validate the impact of our solutions. You will work with other thinkers, creators, and communicators to build the skills of the entire team to create a research-driven organization. You will invent, refine solutions from start to finish—data sets, queries, models, reports, dashboards, analyses—to answer business questions while ensuring we are meeting the needs of the business and team goals. You will draw on your knowledge of data science best practices, big data management fundamentals, and analysis principles to build solutions that enable effective, data-driven business decisions. You will learn the business context and technologies behind your team’s data infrastructure and work with customers (e.g., researchers, economists, data engineers, business intelligence engineers, product managers) and other internal partners to ensure deliverables are aligned with expectations.If you love getting to the “a-ha” moment, when the solution to a customer or employee problem reveals itself in the data— let’s talk!Key job responsibilities• Own the design, development, and maintenance of scalable solutions for analyses and models.• Create innovative, sophisticated analytic models to address critical issues but also meet key business criteria (cost/risk/business impact) and key technical criteria (reliability/validity/predictability)• Lead technical aspects of experiment design in collaboration with the greater ER team.• Find and create ways to measure the workforce experience at multiple levels in the organization.• Identify and advocate for technical options related to machine learning, data mining, and other statistical approaches• Document feasibility requirements, code comments and other technical documentation required to transfer knowledge to other technical staff and management• Write queries and have in-depth knowledge of the data available in area of responsibility.• Troubleshoot operational data-quality issues and review/audit existing ETL jobs and queries.• Collaborate on developing effective Dashboards to surface insights to senior leadership• Communicate pros and cons of analytic frameworks to the development team• Uncover drivers, impacts, and key influences on productivity and innovation outcomes• Develop predictive and optimization models for key applications• Navigate a variety of data sources, such as open text comments, survey results and free text fields inputs• Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes• Maintain an understanding of the latest trends in data science and machine learning• Recommend improvements to back-end data sources for increased accuracy and simplicity.About the teamThe Employee Relations team is responsible for the identification of defects in our employee experience across all roles in the WWC & Ops organization and beyond. Finding these defects is not enough though; we are tasked with building and deploying products, tools and solutions to remove these defects. Our products and programs are always changing and we continually innovate to transform and improve the employee experience.
US, WA, Bellevue
Job summaryThe Amazon Air Science and Technology team is seeking an Applied Scientist to be part of a team solving complex aviation operations problems to reduce cost and improve performance. This is a blue-sky role that gives you a chance to bring optimization modeling, statistical modeling, machine learning advancements to data analytics for customer-facing solutions in complex industrial settings.You will work closely with product, research science and technical leaders throughout Amazon Air, Amazon Delivery Technology and Supply Chain Optimization and will be responsible for influencing funding decisions in areas of investment that you identify as critical future product offerings. You will partner with software developers and data scientists to build end-to-end data pipelines and production code, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, build the machine learning or optimization models that will enable us to continually delight our customers worldwide.The ideal candidate will have extensive experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities. Excellent business and communication skills are a must to develop and define key business questions and build models that answer those questions. You should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges. Further, you must have the ability to build and communicate compelling value propositions, and work across the organization to achieve consensus. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results.Tasks/ Responsibilities:· Partnership with the engineering and operations to drive modeling and design for complex business problems.· Design and prototype decision support tools (product) to automate standardized processes and optimize trade-offs across the full decision space.· Contribute to the mid- and long-term strategic planning studies and analysis.· Lead complex transportation modeling analyses to aid management in making key business decisions and set new policies.
US, WA, Seattle
Job summaryThe F3 (Fresh, Food, Fast) organization enables customers to buy fresh groceries, household essentials, and most popular products from Amazon.com. Our business is global and we lead the innovation in ultra-fast grocery delivery and physical stores experience (Just Walk Out technology) to delight customers more than ever before. As our business is rapidly scaling up, we need to continue developing and improving scalable economic and science solutions to support business growth and better customer experience.We are looking for an economist manager to build a team of scientist and determine the long-term vision for how we set prices in F3. In this cross-functional role, you will partner and work closely with SDEs, business stakeholders, finance, BIEs, and product managers to determine and execute on optimal pricing online and in stores. As a thought leader, you will clearly communicate your vision, models, and results to influence a variety of senior stakeholders. You and your team will apply a battery of economic (demand estimation, casual inference, time series forecasting, etc.) and ML (prediction, outlier detection, cluster analysis, NLP/NLU, etc.) methods. You will own the whole cycle of model development including ideation, prototyping, validation, experimentation, and integrating models into production systems while working with a dedicated team of SDEs.Key job responsibilities· Lead strategic vision for product pricing, define roadmaps, and write PRFAQs, while balancing multiple business objectives.· Build, manage, and coach a high-performing team of economists and scientists; review and audit modeling processes and results.· Set team priorities and help the team to choose the right science methods while balancing delivering high impact with raising the science bar at Amazon.· Lead global complex product launches from a scientific perspective including identifying key milestones, potential risks, and paths to mitigate risks.· Partner and work closely with a dedicated team of engineers to put scientific solutions in a production system.· Write technical and business-facing documents to clearly explain complex technical concepts to audiences with diverse business/scientific backgrounds.