AfroTech logo and headshots of  Dela Agbemabiese, Justin Barry, Nashlie Sephus and Colby Wise.
With AfroTech World occurring this week, we asked some of the company's Black scientists what they consider some of the systemic issues limiting underrepresented minorities from being more involved in the technology industry. We heard from Dela Agbemabiese (lower left), a data scientist, Justin Barry (upper left), applied scientist, Nashlie Sephus (upper right), applied science manager, and Colby Wise (lower right), senior deep learning scientist.
Credit: Glynis Condon

Issues of racial, ethnic and gender diversity are on the agenda at AfroTech World

Amazon scientists provide insights on issues related to lack of involvement of underrepresented minorities in the technology industry.

As CNBC reported earlier this year, six years after initially disclosing diversity reports, major technology companies have made little progress in hiring more minorities, especially Black employees with science and technology skills.

This presents a series of ongoing challenges. According the US Bureau of Labor Statistics (BLS), nearly one-quarter of the country’s total economic output is produced by high-tech industries, and in 2017 BLS projected there would be more than 1 million job openings in computer and information technology over the next 10 years. Moreover, computing occupation salaries are more than twice the median wage for all other occupations, according to BLS.

“When we look at tech and its impact on our economy, and the simultaneous underrepresentation of the Black community, it is a critically important racial and economic justice issue," says Allison Scott, CEO of the Kapor Center. “When the tech workforce and leadership reflects the diverse experiences and backgrounds of our nation, I believe tech can begin to play an integral role in addressing long-standing disparities that exist in this country.”

As of December 31, 2019, Amazon reported that 26.5% of its global workforce identifies as Black/African American, 26.5% Asian, 18.5% Hispanic/Latinx, 1.3% as Native American, and 3.6% as two or more races.  The 26.5% of employees who identify as Black/African American work in both non-technical and technical roles.

This week at AfroTech World, issues related to the lack of adequate racial, ethnic, and gender diversity within the technology industry are on the agenda as leaders in technology and business come together to exchange ideas for creating greater opportunity for Blacks in technology.  Amazon is a Diamond Sponsor of this year’s event, and has a virtual recruiting booth.  

On Nov. 13, the company is hosting a virtual event, “Our Voices, Our Power”, presented by Amazon’s Black Employee Network (BEN) affinity group. Attendees will hear employees share their Amazon journey stories, learn about career opportunities, and enjoy entertainment.

In advance of AfroTech, Amazon Science asked some of the company’s Black scientists what they consider some of the systemic issues limiting underrepresented minorities’ involvement in the technology industry, about some of the issues they have had to overcome in pursuing their science careers, who or what inspired them to pursue their science careers, and what lessons we might take from their individual experiences. 

Dela Agbemabiese is a data scientist within Amazon’s advertising organization. He earned his master’s degree in business administration from Drexel University.

Dela Agbemabiese
Dela Agbemabiese

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Lack of financial resources to stimulate curiosity in tech, lack of mentors or heroes to look up to due to low representation, and societal prejudice hindering opportunities.

Lack of financial resources to stimulate curiosity in tech. I have been fortunate and blessed my entire life.  All gratitude goes to my parents. I was born in Ghana, West Africa. My mom was a nurse, and my dad an economist. Due to the nature of my dad’s work, I got the opportunity to travel a lot as a kid, got enrolled into a course at eight years old to get a Linux command line certificate, and always had access to tech resources. My parents sacrificed to ensure I attended the best schools, and there is not a single thing I ever asked for that I did not get. This may not be the case for all children, whose parents are possibly working hard doing multiple jobs, and in some cases are single parents. If the financial resources I had were similar to that of many minority children, it would be unlikely for me to be where I am today.

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Lack of mentors or heroes to look up to due to low representation. While my dad was heavy on econometrics and I learned a thing or two from him, it was my cousin Martey to whom I looked up. He was brilliant academically, and I always wanted to be like him. He tutored me in math and physics, thus giving me an edge over my classmates. Martey was not my only mentor, in fact, I had many, including Yao Obeng, who helped me nurture my creativity and problem-solving skills. Many minority children may not have mentors or heroes within tech to encourage and inspire interest in tech-related careers. If I did not have these mentors to motivate me, it would be unlikely for me to be where I am today.

Societal prejudice hindering opportunities. Growing up in Ghana, prejudice did not exist from a racial standpoint. Once I moved to the United States for my undergraduate degree, this became a reality. My minority friends and I have had to work twice as hard as our peers to prove we are as good as our credentials. We strived to invalidate stereotypes about minorities through the quality of our work and our work ethic. With everything I do, in the back of my mind I am thinking about how my actions or inactions affect the perception towards minorities: am I enabling some of these unfounded prejudices? Or am I, through my work, educating my peers and superiors? For me, this societal prejudice only began when I came to the United States for my undergraduate degree, but imagine the minority children out there who have had to live with this their entire lives. It sure can get demoralizing.

What are some of the obstacles you had to overcome in pursuing your science career?

Societal prejudice hindering opportunities. I have been lucky to have managers and peers that are inclusive and open-minded, that judge me based on the quality of my work. Rachel McKitrick was my first manager in Amazon. I joined Amazon as a business analyst, despite my previous role as a senior data scientist. I just wanted to join Amazon! Rachel knew my business analyst role was not ideal, and gave me projects that were science oriented, which ultimately enabled my transition to scientist. My second manager, Monica Wu, always made herself available to chat and made me feel like my voice and opinion mattered. My current team managed by Dauwe Vercamer and Andrew Petschek welcomed me with open arms, gave me opportunities to shine and lead within the team. They provide direct feedback that has made me a much better scientist today.

I have had the privilege of learning from a lot of people. Societal prejudice may be harder to solve for, but I believe a good place to start will be to find means for minority youth to gain access to some of the brilliant minds within the technology industry, be it through some virtual teaching programs, or through some mentoring programs. The prejudice may exist, the financial resources may be sparse or non-existent, but with heroes and mentors to look up to, a child’s imagination can be sparked for what could be.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

My dad due to his econometrics background, and my childhood mentors who encouraged me to put math and science ahead of basketball and soccer. Since then, I have had lots of mentors along the way, especially here at Amazon. Individuals such as Leo Razoumov, Pranjal Mallick, Amy Ruschak, John Lafayette, and Oded Netzer, who have helped shape me into a better scientist.

My advice to Black students interested in a STEM career, or other Black scientists is to find mentors, and get them involved in your work. Meet with them once a week for even 10 minutes, and let them influence your work.

Justin Barry is an applied scientist with Amazon’s Prime Video organization. He earned his master’s degree in computer science from the University of Central Florida.

Justin Barry
Justin Barry

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

This is a massive topic with a myriad of associated socioeconomic issues. One issue that jumps to the forefront for me is the schools where leading companies within the tech industry recruit from. Traditionally, these companies have limited their recruitment to top universities where Blacks and other underrepresented minorities comprise a small percentage of the student population. This is beginning to change, but I believe technology companies need to more aggressively expand their recruitment efforts, especially among historically Black colleges and universities (HBCUs).

What are some of the obstacles you had to overcome in pursuing your science career?

One issue is imposter syndrome — the idea that you're not good enough and you’re only in your position because you’ve been given special treatment. Although imposter syndrome is something everyone experiences, I think it’s particularly acute for Blacks given the clear underrepresentation within the technology industry. Imposter syndrome can touch all aspects of your job if you’re unaware, or if you don’t have the tools to deal with it. Not everyone has the tools to deal with it, and I suspect not everyone has correctly identified the problem.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

Video games sparked my interest in computer science, and more specifically artificial intelligence. My undergraduate degree is in computer science and math, and machine learning and AI provide the opportunity to apply my computer science and math skills to real-world applications.

Nashlie Sephus is an applied science manager within Amazon Web Services Ai. She earned her PhD in electrical and computer engineering from Georgia Tech.

Nashlie Sephus
Nashlie Sephus

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Imposter syndrome is one issue I find common within underrepresented minority groups. It’s a feeling of being convinced that you don’t belong in the industry, or within advanced roles in the industry, regardless of your accolades and accomplishments. It is as if they are not real or didn’t happen. This is often due to not seeing many others who look like you in similar or higher positions. ‘You can’t be what you can’t see’ is a common thought. Also, there are few mentors or support systems for these groups, and as a black/female/engineer/scientist, you sometimes feel like the minority of the minority, which further isolates you.  

What are some of the obstacles you had to overcome in pursuing your science career?

At times, I have had to fight for myself and members of my teams for equal pay and advancement in my career. I also have needed to develop mechanisms to be heard when it was difficult to convey messages to those around me. I’m usually quiet and reserved, but over the years I’ve learned how to gain respect from peers by being more outspoken even, or especially, when I disagreed. This is one reason why I appreciate Amazon’s leadership principle: Have Backbone; Disagree and Commit. 

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

I grew up in a house full of women where we often did our own chores, like fixing and repairing things around the house. I was also always going to summer math and science camps in elementary and middle school, especially a summer engineering camp for girls after my eighth grade science teacher recommended I attend. This was when I was first introduced to the various areas of engineering, and fell in love with computer science. Being able to control the hardware with software was fascinating to me. I knew then that’s what I wanted to do. This early exposure to science was key to me figuring out one of my passions, in addition to music and sports.

Colby Wise is a senior deep learning scientist and manager within the AWS Machine Learning Solutions Lab. He earned his master’s degree in computer science from the Columbia University Fu Foundation School of Engineering and Applied Sciences.

Colby Wise
Colby Wise

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Educational opportunity. Science, technology, engineering, and math (STEM) careers in the technology industry are highly competitive. Over the years, we’ve seen advanced tools and technologies like cloud technology, machine learning, and deep learning, that were once reserved only for large companies or prestigious universities being utilized by students as early as junior high school. While this has created and accelerated educational opportunities for millions of students globally, the reality is that not all have been able to benefit. In the United States, public school funding varies significantly by geography, and where you grow up is a major factor in access to educational resources. Schools with advanced STEM courses and other after-school programs are valuable inroads for STEM students to accelerate their learning opportunities and explore careers in science. What’s more, these opportunities compound positively from lower educational levels to higher educational levels. While not the only factor, these programs are important when understanding the pipeline of underrepresented minorities in highly competitive industries like technology. For example, the US Federal Reserve conducted a study highlighting how educational attainment of parents plays an important role in children’s educational pursuits. Studies like this and others indicate that lower parental educational attainment may present a unique challenge for students. One potential consequence of underrepresentation of minorities in advanced degrees is that employment opportunities often arise from one’s social network, employee referrals, for example. This can be summarized as both an employment funnel problem and a network problem. While not always the case, a more diverse workforce can build connections to underrepresented talent pools. 

Financial equality. In a study from 2020, the US Federal Reserve found large and persistent gaps in net wealth and earnings by race and ethnicity. While education is a significant factor in wage gaps, the St. Louis Federal Reserve found net wealth by race was not as positively correlated with educational attainment for minorities. Educational attainment is extremely important. Many highly technical roles require advanced degrees. Financial equality and opportunity as characterized by job salary prospects, current income and net wealth, and access to educational funding sources like loans are all potential factors impacting lower minority employment. In 2016, the Brookings Institution found the median household net wealth for Black and Hispanic families to be 1/8th  that of white households. When you consider the rising cost of college and advanced degrees, this income and net wealth gap may also play a factor in why employment among underrepresented minorities is lower in highly competitive industries like technology. Specifically, minorities whose households cannot readily pay for advanced degrees choose between the implications of high debt burdens and lower comparative earnings, and often must forsake advanced degrees to enter or stay in the workforce.

Leadership representation. Representation of minorities in leadership positions is relatively low. It is unclear how much educational opportunity and financial equality contribute to this, compared to other issues such as equitable pathways to senior leadership positions. In many companies in which I have worked, you notice a similar triangular pattern of minority leadership where representation at junior levels is more in-line with industry trends, while there is a dearth of representation as you reach more senior positions. No doubt there is work to be done to drive greater employment of underrepresented minorities at all levels. But simply increasing the representation at entry levels does not address other attrition and talent-retention hurdles. Overall, companies need to take a more systematic, data-driven approach to move the needle and find solutions to underrepresentation of minorities in the tech industry. For instance, companies should not be afraid to tackle the complex issues at multiple hierarchies, such as creating innovative solutions to drive educational opportunity while objectively measuring current pathways to employment within the tech industry. Furthermore, companies should ensure financial equality by aligning corporate incentives with fair pay distributions, minority leadership representation, and talent development and retention.  

What are some of the obstacles you had to overcome in pursuing your science career?

Educational opportunity. While everyone’s path is different, unfortunately my story is rather common given its similarity to those of many underrepresented minorities. I faced and overcame obstacles in educational and financial opportunity plus roadblocks to leadership roles. I attribute my luck mainly to the many individuals who provided a helping hand, plus a little bit of hard work sprinkled in. I grew up in a single-parent household in an impoverished, high-crime inner-city area. Despite this, my family valued education highly, and one of my parents had an advanced degree which was extremely rare for the area. Given that, I always ranked in the top 1% in my coursework while very young. That said, district educational attainment rates were low, and advanced coursework or programs for gifted students were nonexistent. However, prior to high school an unfortunate family event led to me moving from one of the poorest areas in the country to one of the best school districts nationally. After discovering how far behind I was in math and science, my family and I worked extremely hard over several years to get me back in line with my expected academic grade level. Now fast-forwarding to college: I, like many other minorities, did not have the means to pay for college, nor easy access to loans. After being selected to a number of great schools, my decision was ultimately driven by the amount of money I received in scholarships and grants. During college I followed the same recipe for success: tons of luck, humility to ask for help, and a bit of hard work to land an internship as a sophomore at a prestigious Wall Street investment bank. There I was surrounded by some of the smartest minds in STEM, with many having achieved advanced degrees from top universities around the world. The vast majority of these individuals did not look like me. Desperately wanting to be accepted and succeed among my peers in industry is what drove me to pursue a career in science, and many years later brought me to AWS.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

Family and friends. Ultimately, doing what you love and constantly learning while being curious is the greatest inspiration one needs to pursue a career in science. As discussed above, studies have shown a correlation between parental educational attainment and children’s attainment. Thinking forward a bit, I combined my passion for what I love in science — AI/ML — with a selfish goal of wanting to be a living model for a career in science for my children. My greatest inspiration, however, is my wife. She discovered her passion for science at a very young age with plentiful opportunities to explore that passion, ultimately helping her reach the pinnacles of academia, where she received undergraduate and graduate degrees from two of the top universities in the world. Her passion for science, hard work, and humility continue to inspire me on a daily basis.


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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.