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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We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data 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 like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.Major responsibilities· · Use machine learning and analytical techniques to create scalable solutions for business problems· · Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes· · Design, development, evaluate and deploy innovative and highly scalable models for predictive learning· · Research and implement novel machine learning and statistical approaches· · Work closely with software engineering teams to drive real-time model implementations and new feature creations· · Work closely with business owners and operations staff to optimize various business operations· · Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· · Mentor other scientists and engineers in the use of ML techniques
US, CA, San Diego
.A day in the life.About the hiring group.Job responsibilitiesEconomistThe North American Consumer Economics team uses Economics, Statistics, and Machine Learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon.We are looking for an outstanding Economist who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.In this role, we expect you be able to own the development of economic models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.We are particularly interested in candidates with research background in applied microeconomics, empirical IO, Marketing, Finance, applied econometrics, and market design. However, we want to talk with any experienced economist with an interest in working on an interest in working on innovative, strategic problems with significant business impact.Amazon 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.
CA, BC, Vancouver
Are you passionate about driving business & customer impact through thoughtful analysis and data-driven insights? Are you a deeply technical individual who enjoys working with customers to transform how a business operates? Are you a builder that excels with ambiguity? Are you inspired by invention? Is problem solving through teamwork and working in a startup environment in your DNA? Do you like the idea of seeing how your work impacts the bigger picture?Answer yes to any of these and you’ll fit right in here.We are looking for Data Scientist professionals to drive our analytical revolution in the Talent Acquisition (TA) space. You get the opportunity to work on a ground up rebuild of our analytical capabilities, from data ingress, to complex business transformations to end user reporting and beyond. In this role, you will invent and build on behalf of candidates, experiment and test new ideas, evangelize successes, and drive consistency.The ideal candidate is an independent Data Scientist who can source data, cleanse, analyze, refine, enrich, model, present, automate and document our business data pipelines. You will always be on the lookout for ways to optimize the information flow process, stay on top of latest trends in data warehousing and be able to coordinate and work on multiple, related projects.Responsibilities:· Collaborate with recruiting operations, data scientists, and business leaders to define business processes and provide analytical support· Leverage code to analyze complex datasets and design, develop and evaluate data transformations to solve specific business problems· Build scalable, efficient, and automated data processes to facilitate customer-facing reporting· Automate TA processes to streamline business operations· Communicate verbally or in writing to business customers / leadership to sharing insights and recommendationsThis role can be based out of any US/Canada AWS Corporate location (i.e. Seattle, WA, Arlington, VA, Herndon, VA, New York, NY, Boston, MA, Chicago, IL, Dallas, TX, Cupertino, CA, Palo Alto, CA).
LU, Luxembourg
At Amazon, we strive to be the most innovative and customer centric company on the planet. Come work with us to develop innovative Customer Fulfilment products, tools and research driven solutions in a fast-paced environment by collaborating with smart and passionate leaders, program managers, data scientists and software developers. Our mission is to build the most efficient, intelligent and interpretable solutions on the planet.The EU Ops Integration Analytics team is part of Amazon EU Customer Fulfillment and is responsible for improving and supporting performance management of our Fulfilment Centers through state-of-the-art and scalable analytics solutions. We work backwards from the customer and define new innovative solutions that raise the bar on customer experience whilst constantly lowering our cost and supporting our continued growth.We are looking for a thought leader and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business with data driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a big impact. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence and interact with broad range of stakeholders (technical and non-technical). You draw from a broad data science expertise to mentor Data Scientists and Business Intelligence Engineers; following a rigorous scientific methodology, while providing leadership on complex analytical topics. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modeling decisions. We expect you to have breadth of data science knowledge, and depth in predictive modeling (supervised learning) and unsupervised learning (clustering).Key Responsibilities· Develop predictive models and decision science to guide program and operations teams on improving our customer experience (e.g. predicting concessions and optimizing the best action to take, sustainability and energy etc.)· Drive data science best practices and mentoring junior team members based on your in-depth knowledge in theoretical and practical data science disciplines.· Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon’s data resources, industry best-practices, and work done by other teams.· Partner with, coordinate, and influence multiple teams outside of EU Customer Fulfillment (Customer Service, Transportation, Amazon Logistics.), to support key initiatives.· Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes.· Drive and promote experimentation culture (e.g. A/B testing) with data-driven mindset and measurable approach.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching?Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on.The Research & Insight team operates in a dynamic and entrepreneurial environment across Europe and the world to understand our customers holistically. We work with senior stakeholders across a wide range of functions to plan, execute, and deliver continuous knowledge and insight to marketing and business teams to deliver customer centric growth.We are looking for a Sr. Data Scientist, Market Research to build our data strategy from the ground up. In this role, you will define quantitative research data standards and structures for end-to-end research processes, ensuring fit for purpose databases that are widely accessible and in usable formats for a variety of stakeholders. You will architect tools such as dashboards and automated reporting to help democratize our market research data. You’ll leverage predictive models, advanced machine learning/AI capabilities and exploratory data analysis (EDA) to solve problems and deliver insight.Responsibilities· Collecting and structuring data from a variety of 3P agency partners and APIs.· Collaborate closely with research, marketing, finance and content partner teams to ensure your data roadmap is fit for purpose across stakeholder groups.· Define and develop data management platforms, analysis tools and user friendly dashboards and reports.· Conduct ad-hoc analysis and predictive modelling to extract value from data to uncover opportunities and recommend actions.· Visualize data sets to inspire stakeholders (word clouds, infographics).· Perform regular data and system audits and feedback to ensure complete, accurate and usable data.· Optimize self-serve platform for data reporting and analysis to accelerate information-to-action at scale.· Build capability training across data and tools.· An SME for research data platform tools and analysis capabilities and delivery.
US, WA, Seattle
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 Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.Worldwide Ad Success team (WASE) is at the forefront of our amazing growth machine enabling our teams to deliver at scale. Our goal is to scale account management multifold by investing in strategic self-service applications that improve productivity of external advertising customers and internal account management executives. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.As part of our team evolution we are investing in improving our understanding of the advertisers on Amazon through advanced ML modeling and building an ML service that delivers recommendations to advertisers and solves the prioritization and selection of most optimum recommendations and measure impact with explain-ability.We are moving fast and have the ability to shape our tech infrastructure that will combine science and scalable engineering at a rapid pace. We are looking for a senior Applied Scientist to join the team to drive key science methods and delivery of the project, working closely with product and engineering leads, as well as our leadership. This is a relatively new team, with a focused initiative. We’re a fast-growing team with high visibility from the leadership team and lots of new opportunities.As an Applied Scientist on this team you will:· Solve business problems using state of the art machine learning methods.· Work on full life-cycle projects - from researching the optimal machine learning models to use to deploying your models into production.· Drive processes, tools, and statistical methods that support rational decision-making.· Be technically fearless: You aren't satisfied by performing 'as expected' and push the tech teams past conventional boundaries. Your dial goes to '11'.· Help grow recruit other scientists to achieve outstanding results.· Foster a creative atmosphere to let engineers and other PMs innovate, while holding them accountable for making smart decisions and delivering results.· Explore new problem spaces with unique constraints and thus non-obvious solutions; identify any gaps in the solutions and/or approach.Why you love this opportunityAmazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit. With a broad mandate to experiment and innovate.Impact and Career GrowthYou will invent new shopper and advertiser 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 fundamentally 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_6Lzw8raEAmazon 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, VA, Arlington
Amazon Global Talent Management (GTM) Science is an innovative organization that exists to propel Amazon HR towards being the most scientific HR organization on earth. The GTM Science mission is to use Science to assist and measurably improve every talent decision made at Amazon. We do this by discovering signals in workforce data, deploying statistical models into Amazon’s talent products, and guiding the broader GTM team to pursue high-impact opportunities with tangible returns. This multi-disciplinary approach spans capabilities, including: data engineering, reporting and analytics, research and behavioral sciences, and applied sciences such as economics and machine learning.We are seeking a Senior Research Scientist with deep quantitative and qualitative research expertise in Diversity, Equity, and Inclusion (DEI) and the Future of Work (FoW). This person will possess a strong mixed methods background, knowledge of different approaches to evaluating fairness in employment decisions, and experience with analyzing DEI data. In this role you will:· Design, develop, and execute quantitative and qualitative data collection methods in future of work, DEI, and related talent management efforts· Conduct quantitative analyses of DEI data and trends· Conduct qualitative data collection and analysis· Partner closely with Amazon Global DEI teams· Partner closely and drive effective collaborations across multi-disciplinary research and product teams· Manage full life cycle of large scale research programs related to DEI
US, CA, East Palo Alto
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc., an Amazon.com CompanyTitle: Applied Scientist IILocation: East Palo Alto, CAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, WA, Seattle
We are a passionate team working to build a best-in-class healthcare product designed to make high-quality healthcare easy to access.We are looking for a truly innovative and technically strong applies scientist with a background in machine learning and natural language understanding.As a Senior Applied Scientist, you will:· develop models for various natural language processing tasks, including named-entity recognition, natural language inference, sentiment analysis, text summarization, and question answering within in a healthcare context· work closely with product managers to expand the depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps· provide technical and scientific guidance to your team members· ensure that teams are collecting, understanding, and using data to inform every decision that impacts our customers· stay current with advancements and the latest modeling techniques in the field· publish your research findings in top conferences and journalsAbout You:· Problem Solver: Ability to utilize exceptional problem-solving skills to work through different challenges in ambiguous situations.· Doer: You’ve successfully delivered end-to-end AI/ML projects, working through conflicting viewpoints and data limitations.· Detail Oriented: You have an enviable level of attention to details, and catch things that others miss.· Communicator: Ability to communicate analytical results to senior leaders, peers, and external customers.· Influencer: Innovative scientist with the ability to identify opportunities in a fast-paced and ever-changing environment, and gain support with data and storytelling.Here at Amazon Care, we embrace our differences. We are committed to furthering our culture of inclusion. 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well- balanced life—both in and outside of work.Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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
Sponsored Products (SP) is Amazon's largest and fastest growing ad business. SP ads are shown prominently throughout search and product detail pages and allow shoppers to seamlessly discover products sold on Amazon. These are native ads that appear visually similar to other content on the page, which presents a huge opportunity for growth and impact, but also a significant responsibility to protect shopper experience.Job Responsibilities:· Design, develop, and deploy machine learning solutions.· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines.· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior leaders.· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation.· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences.Impact and Career Growth:· Opportunity to grow and broaden your machine learning skills a make impact – the work you deliver directly impacts customers and revenue!· Work in an environment that thrives on creativity, experimentation, and product innovation.· Drive real-time algorithms to allocate billions of ads per day in advertising auctions.· Have the ability to experiment autonomously with meaningful projects.· Mentor others.Why you love this opportunity:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
SG, Singapore
The Amazon Prime Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply economic and econometric theories to large-scale business problems and big data sets.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will work in a team of economists, data scientists, and engineers and in collaboration with product and finance managers. These experiences will translate well into writing applied chapters in your dissertation and prepare you with placement in academia or private sector.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Interested in using AI to improve the shopping experience of millions of customers? Amazon Search has the perfect job for you.Amazon Search Customer Experience is looking for an experienced scientist to lead the innovation in Search Whole Page Optimization (WPO). Your research spans deep learning, reinforcement learning, and personalized recommendations. You will work with a team of scientists and engineers to make Amazon’s search experience intelligent, intuitive, and enjoyable.A successful candidate has strong customer obsession, highly-cited publications in relevant areas, and a track record of deploying research outcomes in production. You will bring deep technical expertise and strong business acumen. Amazon leaders are visionaries who are not afraid of rolling up their sleeves and getting their hands dirty. You will help shape the future of Amazon’s search customer experience by painting a compelling vision and leading the journey to get there. You must have the desire to make industry-wide impact and the ability to work within a fast moving environment to rapidly deliver innovations.As a senior leader, you will be responsible for the holistic optimization of Amazon search pages. From page layout to content ranking, from the navigation experience to product display optimization, you will rethink the assumptions behind traditional e-commerce experience and leverage AI to make the shopping journey of each customer a delightful one. You will be part of the Search technical leadership community that forms the backbone of the company. You will play a critical role in business planning, work closely with senior executives, and influence our long-term technical and business strategy.If you like the challenges and opportunities in this exciting space, come join us to work hard, have fun, and make history.
US, WA, Seattle
The Amazon Shipping is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply what they've learned in an academic setting to a business environment, specifically focused on time series forecasting for routing problems.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
Amazon is looking for a creative Senior Research Scientist to tackle some of the most interesting problems on the leading edge of natural language processing (NLP), machine learning (ML), search and related areas with our Alexa AI team. Alexa AI aims to reinvent search and information retrieval for a voice-forward, multi-modal future. It enables customers to interact with unstructured and semi-structured content via a broad range of technologies including question answering, summarization, search, and multi-turn dialogues.If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel scalable algorithms and modeling techniques to advance the state-of-the-art in technology areas at the intersection of ML, NLP, search, and deep learning. You will innovate, help move the needle for research in these exciting areas and build cutting-edge technologies that enable delightful experiences for hundreds of millions of people.In this role you will:· Work collaboratively with other scientists and developers to design and implement scalable models for accessing and presenting information;· · Drive scalable solutions from the business to prototyping, production testing and through engineering directly to production;· · Drive best practices on the team, deal with ambiguity and competing objectives, and mentor and guide junior members to achieve their career growth potential.