Howard University's Founders Library is seen in the distance.
Howard University's Founders Library is seen in the distance. Howard is hosting AEASP “in support of increasing the pipeline of underrepresented minority economists.”
Oscar Merrida IV

Amazon to sponsor Howard University summer program aimed at increasing pipeline of minority economists

Howard University is the first Black college to host the American Economic Association Summer Training and Scholarship Program.

Howard University recently announced that it will host the American Economic Association Summer Training and Scholarship Program (AEASP) “in support of increasing the pipeline of underrepresented minority economists.” The program will be hosted at Howard for the next five years, and Amazon is sponsoring next summer’s program. Amazon first began discussions with Howard University about sponsoring AEASP about two years ago. The program, which aims to prepare “talented undergraduates for doctoral programs in economics and related disciplines,” will celebrate its 50th anniversary in 2024 at Howard.

"The lack of diversity in economics becomes self-reinforcing"

Four economists from diverse backgrounds shared how economics can address its diversity problem and talked about how their lives have shaped their work as economists.

That Howard, an historically Black college and university (HBCU) which produces more Black economics undergrads than any other institution, is hosting AEASP for the first time serves as a reminder of the progress the economics profession still must make.

The Caucus of Black Economists (later called the National Economics Association) first began exploring the issues of underrepresentation of minorities within the economics field in 1969. More than 50 years later, the economics profession is still grappling with structural issues. In fact, last January’s AEA conference in San Diego featured a panel titled, “How Can Economics Solve Its Race Problem.”

Rhonda Vonshay Sharpe and Omari H. Swinton standing in front of Howard University.
Rhonda Vonshay Sharpe, left, and Omari H. Swinton, right, are seen posing on the campus of Howard University. They discussed why economics still struggles with diversity.
Oscar Merrida IV

Omari H. Swinton, the chair of Howard University’s Department of Economics, who is both an alumni and the current director of the AEA summer program, as well as the past president of the National Economics Association, has observed that, “The vast majority of institutions in the US have never had a Black economist on staff, and the vast majority of schools have never graduated a Black PhD economist.”

Rhonda Vonshay Sharpe, the founder and president of the Women's Institute for Science, Equity, and Race (WISER), which is also a partner in next summer’s AEASP program, authored a research paper in 2019 that found that from 1966 to 2015, “the number of undergraduate economics degrees conferred to Black women was stagnant, and there was a decrease in the number of doctorates conferred to Black men.”

So why does the economics field still have such a massive disparity in minority representation? What needs to happen for systemic progress to be made? Amazon Science sat down with Sharpe and Swinton to ask those questions, as well as why Howard hosting the summer program is so significant, and what advice they would give to students considering economics as a major or profession. We also talked with Amazon chief economist Pat Bajari to find out why Amazon is sponsoring next summer’s AEASP program, and why he thinks diversity within the economics profession is essential.

A Howard University sign on the Howard campus
The AEASP will celebrate its 50th anniversary in 2024 at Howard University.
Oscar Merrida IV

Why does economics still have such a significant diversity problem?

Omari H. Swinton: I don't know that economics, as a profession, has really agreed that there's a problem. I think that's one of the big issues—we’ll say there's a problem, but nothing ever changes. You oftentimes hear people say things like, ‘We want to increase diversity’ but don't actually make any changes. They just say that that's something that they want to do.

It’s not as if these things haven't been out there. There are people out there who have dedicated their lives to bringing these types of issues to the forefront. I go back to Sandy Darity as an example. If you read from his earlier work, he's talking about these issues. Gregory Price has chronicled which institutions have Black economists in them. Rhonda has been looking at these issues for years.

Whether the economics profession is really ready to change is the issue. There have been a lot of people who have been talking about these issues for years. Others have come out and mentioned these problems more recently, but they ignore the fact that people have been talking about issues of underrepresentation for years.

Rhonda Vonshay Sharpe on the campus of Howard University
Rhonda Vonshay Sharpe says economics needs to define what diversity means. "If you don't define it, you can't measure it, or hold folks accountable."
Oscar Merrida IV

Rhonda Vonshay Sharpe: I narrow the problem down to be three things: 1) Economics has never defined what diversity means, and if you don't define it, you can't measure it, or hold folks accountable; 2) We don't have accurate data to track progress. We need to collect data that can be disaggregated by characteristics that have been used to limit participation in the profession. For example, when you talk about women, that usually means white women, and when we talk in terms of race, then you're really talking about men, and both of those descriptors are biased; and 3) As Omari said, there's enormous erasure happening. People have been doing this a long time, yet newcomers who have recently gotten tenure suddenly feel bad. They are handed a mic as if they are now the authorities. They don’t bother to understand whose shoulders they're standing on.

What needs to happen to address this problem? What role can academic institutions and companies like Amazon play?

Sharpe: I don't think the answer is to hire more Black economists. I really don't. And here is why: Because I think that when people say, ‘hire more Black economists’, people do just that, they hire Black economists. They do not think about whether or not those Black economists are bringing lived experiences that are going to help you craft policies to better interact with your customers.

One of the things I've been saying to folks recently is we need to talk more about structural classism and the ways in which we treat folks who are poor. So, it's not just about hiring Black economists, it's not about hiring Hispanic economists. It's about hiring folks who have lived experience in the US that will get at the inequality and related issues. That's not going to be solved just by hiring an economist because they are non-white.

Omari H. Swinton, the chair of Howard University's Department of Economics, on Howard's campus.
Omari H. Swinton says the AEASP program coming to Howard "is important because this is what our program is designed to do: increase minority participation in the economics profession."
Oscar Merrida IV

Swinton: If you say you want to diversify the profession, then stop looking at things that are not really problems. For example, there's not really a pipeline problem. You can ask almost any economics professor who teaches Principles of Economics, and most will tell you that is probably one of the worst classes to use if you want somebody to be interested in economics as a profession. But it really hasn't changed in years.

One change that we're making in the summer program is the experiential internship, or experiential learning. We’re going to place students with think tanks and corporations to actually see what an economist outside of the academy does. Everybody that gets a PhD in economics isn't going to be able to get a job as a professor. What does it look like to be an economist at Amazon? What does it look like to be an economist at the Census Bureau or at Brookings? Those are entirely different experiences. We’re trying to partner with as many different organizations as possible.

Hopefully we'll see change at those institutions, because students will come to the summer program, have that experience, and want to go back to those institutions. Rather than wanting to be a professor, they will, for example, say, ‘I want to be an economist at the Census Bureau, because I believe this research is important.’ It’s important for organizations, public and private, to be available to students, so they can see the type of experiences they can have if they work for you.

Pat Bajari
Pat Bajari, Amazon vice president and chief economist
Carl Clark, Amazon Imaging Studio

Pat Bajari: As an economist, I have always thought of this is in terms of diminishing returns. If you always have the same type of viewpoint, and keep hiring replicas of that viewpoint, the returns you get from that eventually decrease. Having different viewpoints allows you to do better work. And because we serve a large and diverse base of customers, we have a large and diverse base of problems. We want to take a leading role in supporting a new generation of economists from underrepresented minorities—it is not only the right thing to do, but it will also help bring strong and diverse voices that will create an even more inclusive customer experience.

When individuals come from different backgrounds, they bring different perspectives to the table. You do better work when you have different perspectives.
Pat Bajari

Swinton: One thing organizations can do is find programs that are actually successful at achieving the types of goals they’re pursuing. For example, some of the research done by Becker et al. shows that about 20 percent of Blacks that have PhDs in economics have attended the AEASP program. By helping support Howard in hosting AEASP in this first year, Amazon is doing that. Without Amazon’s support, Howard wouldn't be able to host the AEA summer program at all. We certainly hope others will follow Amazon’s lead.

What is the significance of the summer program coming to Howard?

Swinton: The summer program is extremely important in my path as an economist. My first cohort of economists were the people that I met through the summer program. Howard is the number one producer as an undergraduate feeder of Blacks who go on to get PhDs in economics. This is our mission and one of our goals as an institution and as a department, and I think the AEA summer program coming to Howard is important because this is what our program is designed to do: increase minority participation in the economics profession.

The National Economics Association summer program came out of Marcus Alexis’ mind as a program to help get minorities interested in economics. For the AEASP program to come to Howard at this point in time is a great honor. It’s an honor to be the first HBCU to host the summer program.

Sharpe: I'm excited to see a program that's going to be led by Blacks, which I think is incredibly important, as the program will celebrate 50 years while it's at Howard in 2024. It just feels full circle in terms of thinking about Marcus Alexis, who was a Black economist, and then having the program 50 years later be at an institution that is the number one producer of Black economists. That's incredibly exciting.

Finally, what advice would you give to someone considering whether to pursue a degree in economics? Why is economics such an important field?

Bajari: A lot of economics is understanding people's material wellbeing. Who has low wages? Who has high wages? If you take a given policy, whether that's central bank policy or interventions into labor markets, etcetera, these things deeply, deeply, deeply affect people's lives, people's material outcomes. What they can purchase and where they can live and where they can send their kids to school and so forth. It's an important set of questions, and they range from micro things about what happens to the individual, to macro things, such as how the whole world is evolving and changing in response to things like COVID-19.

Howard University's Founders Library
Howard University's Founders Library is seen here. Howard is the first Black college to host AEASP.
Oscar Merrida IV

If we change policy or somebody goes to college versus doesn't go to college, what are the implications of those economic variables? I know this is what attracted me to economics. As a young person, growing up pretty poor in rural Minnesota, I was interested in the world and how it worked. And I liked economics because it brought math and data and scientific formalism to those questions. That's not the only way you can look at those questions, or the only way you should look at them, but it’s one way that's highly useful.

Sharpe: For students pursuing a PhD in economics, my main advice is to pick a PhD program that's a good fit for you. Many students think that if you don't go to a top program, you can't have a successful career. That’s not true. I went to Claremont Graduate University, not highly ranked, but I had an amazing time as a graduate student. I loved it. My mentee when I was in graduate school was Olugbenga Ajilore who’s at CAP (Center for American Progress) now, who is a rock star right now in terms of being in the news and asking people to think about rural communities. He and I didn't go to top economics departments, but we went to places that were good fits for us, and that's incredibly important.

Bajari: “Technology economics” is a booming field. The largest conference held by the National Association of Business Economists is now the tech economics conference. It’s larger than their annual conference now, because it's been an explosive area of job growth for young people. We are one of the larger private sector employers of economists. When you're in that role, you have an obligation to demonstrate leadership. We saw sponsorship of AEASP as an opportunity to expose young PhDs to this emerging field. I thought Howard was very thoughtful about their proposal, and I'm hoping AEASP can help us establish a pipeline of highly qualified candidates.

Swinton: I talk to students about this all the time. You want to make a change, and you want to be a policy maker? Be an economist. You want to go into business and work on Wall Street, make a lot of money? Be an economist. Economics is one of the most useful majors because it allows you the opportunity you to go out and do a wide variety of things based on the basic training you obtain.

Applications for the summer program are open and the deadline to apply is January 31, 2021. To apply, visit economics.howard.edu/aeasp. The program will be held May 27 to July 25, 2021, and be offered in Washington, D.C., contingent upon COVID-19 restrictions.

Research areas

Related content

US, WA, Seattle
Interested in influencing what customers around the world see when they turn on Prime Video? The Prime Video Personalization and Discovery team matches customers with the right content at the right time, at all touch points throughout the content discovery journey. We are looking for a customer-focused, solutions-oriented Principal Data Scientist to develop next-gen measurement and experimentation systems within Prime Video Personalization and Discovery. You'll be part of an embedded science team driving projects across product and engineering teams that ultimately influence what millions of customers around the world see when the log into Prime Video. The ideal candidate brings experience building experiment-based measurement systems at scale, excellent stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video for high-quality, rigorous measurement, assess business problems, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Define and drive the multi-year vision for experiment-based measurement systems within Prime Video - Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience - Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Mentor junior scientists and review technical artifacts to ensure quality - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization
US, WA, Seattle
Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for an Research Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market. Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects. As a Research Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership. Key job responsibilities - Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network. - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics. - Develop end-to-end solutions, tools and frameworks to scale our ML model development and data analysis. - Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features. - Present research findings and recommendations to scientists, business leaders, and executives. - Collaborate with cross-functional teams to drive adoption of models and insights. - Stay current on latest developments in relevant fields and propose innovative approaches. About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.
IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are seeking a technical leader for our Search Thematic Advertising Experiences team to lead a multi-disciplinary team of science and engineering. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Thematic Advertising Experiences , within Sponsored Products, is seeking a Senior Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Applied Scientist on this team you will: --Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. --Lead technical efforts within this team and across other teams. --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --Run A/B experiments, gather data, and perform statistical analysis. --Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. --Recruit Applied Scientists to the team and act as a mentor to other scientists on the team. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.
US, CA, Culver City
Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. We are seeking a highly skilled and analytical Research Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing causal models and randomized controlled trials to assess marketing effectiveness and inform strategic decision-making. This role is suitable for candidates with strong background in causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth. Key job responsibilities Develop Causal Models Design, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships. Conduct Randomized Controlled Trials Design and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights. Statistical Analysis and Inference Perform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns. Data-Driven Decision Making Collaborate with marketing teams to provide data-driven recommendations that enhance campaign performance and ROI. Present findings and insights to stakeholders in a clear and actionable manner. Collaborative Problem Solving Work closely with cross-functional teams, including marketing, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization. Stay Current with Industry Trends Keep abreast of the latest developments in data science, causal inference, and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement. Documentation and Reporting Maintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.
US, WA, Seattle
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. The Data Center Field Engineering Team is the engineering owner for the lifecycle of AWS data center mechanical and electrical infrastructure. This includes supporting new designs and innovations through data center end-of-life, with a focus on root cause analysis of failures, capacity and availability improvement, and optimization of the existing fleet. As a Senior Data Scientist on the Field Engineering Portfolio team, you will bring advanced analytical and machine learning capabilities to one of the most critical infrastructure organizations at AWS. You will develop scalable models and data-driven frameworks that measure, predict, and improve fleet performance — including data center availability, operational efficiency, and key performance indicators (KPIs) across the global AWS data center fleet. You are an exceptionally strong communicator, both written and verbally, capable of translating complex quantitative findings into clear recommendations for senior engineering and business leadership. You will work cross-functionally with Field Engineers, Operations, Commissioning, and Construction teams to ensure that data science solutions are grounded in operational reality and drive measurable impact. You will partner with engineering teams and program managers to define metrics, identify performance gaps, and build the analytical infrastructure needed to support strategic decisions at hyper-scale. You must be adept at operating in ambiguous, fast-moving environments where speed of insight can matter as much as analytical precision. The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will develop scalable analytical approaches to evaluate performance across the data center fleet to identify regional and site-specific insights, design and run experiments, and shape our development roadmap. You will build cross-functional support within the Data Center Community to assess business problems, define metrics, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities • Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio. • Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.). • Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations. • Design and implement end-to-end data science workflows — from data acquisition and cleaning through model development, validation, and production deployment — enabling repeatable, scalable analysis. • Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities. • Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance. • Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities. • Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.