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, left, the founder and president of the Women's Institute for Science, Equity, and Race (WISER), and Omari H. Swinton, right, the chair of Howard University’s Department of Economics, and the current director of the AEA summer program, discussed why the economics field has a massive disparity in minority representation, what progress can be made, and why they're excited that Howard University is hosting the AEA's Summer Training and Scholarship program.
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 is seen 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 is seen 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, is seen 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 portrait
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 is seen here
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.

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The Amazon Devices team designs and engineers consumer electronics, including the best-selling Kindle family of products, Fire tablets, Fire TV, Amazon Dash, and Amazon Echo.As an Applied Scientist, you will participate in the design, development, and evaluation of models and machine learning (ML) technology to delight our customers.You will be part of a team delivering features that are well received by our customers.
US, WA, Seattle
Workforce Staffing (WFS) supports Amazon Operations by hiring the hourly associates that staff our operational buildings. WFS is quickly becoming one of the world’s largest staffing organizations, forecasted to hire over one million hourly associates across North America and the European Union this year alone. Currently, we hire full time, part time, flex time and seasonal hires across Fulfillment Centers, Sort Centers, Amazon Logistics, Whole Foods, Amazon Air, Prime Now, Amazon Fresh, and emerging business lines. Interested in the businesses that Amazon creates and grows? Here’s your opportunity to be a part of this journey.The Workforce Intelligence team was created in 2018 to support the massive growth in scale and scope that WFS has experienced. The team has continued to grow rapidly in order to meet the expanding needs of the business, including: big data and machine learning solutions, innovative approaches to complex HR problems, and data-driven recommendations during a time of rapid change.Here’s where you come in:As a Research Scientist in Workforce Intelligence, your work is focused on research to deeply understand the people that make up our hourly workforce and help others do the same. You understand that even when hiring hundreds of thousands of hourly associates across multiple types of roles and businesses, the experience of each candidate matters.You use your deep expertise in surveys and statistics (regressions, multilevel models, etc.) to define and answer nebulous problems. You use experimental, quasi-experimental, and RCT methods to understand our candidates and influence critical business decisions. You relentlessly obsess over understanding our candidates and lead our survey program that seeks to amplify the voice of our candidates. You work with colleagues across Research, Data Science, Business Intelligence and related teams to enable Amazon find and hire the right candidates for the right roles at an unprecedented scale.This will be a highly visible role across multiple key deliverables for our global organization. If you are passionate and curious about data, obsess over customers, love questioning the status quo, and want to make the world a better place, let’s chat.
US, WA, Seattle
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.Please visit https://www.amazon.science for more information.At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday life.What you will do: You will lead a team of talented and experienced scientists and engineers that implement solutions for natural language understanding of Alexa Shopping customers: this involves taking the outputs from automated speech recognition (ASR) component and producing a representation of its meaning. Additionally, your team will build Alexa Shopping Automated CX quality metrics and provide analytics. This involves exploring, developing, socializing, and implementing mechanisms for tracking automated CX quality across customer’s journey with Alexa Shopping to improve Alexa Shopping CX. And finally, you will have the satisfaction of being able to look back and say you were a key contributor to something special from its earliest stages. You will be working closely with executive leadership, multiple product managers and leaders from partner teams in Amazon Retail, Alexa, and Speech Recognition teams.What we are looking for: We are looking for a talented Data Science Manager with a strong technical background and solid people management skills to build, manage and develop a highly-talented and experienced data science team. We are seeking leaders that can guide technical and product innovation in the areas of voice experiences, machine learning models and the distributed systems to bring our vision together. Strong judgment and communication skills, long term technical vision, and continuous focus on engineering and operational excellence are essential for the success in this role.
DE, BE, Berlin
As a Senior Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search engine. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages, not only English and major languages of Europe, but also Turkish, Arabic, Japanese, and more. The team plays a central role in search query understanding, product indexing, and representations/embeddings of queries and products, all of which aid in improving the ranking and relevance of search results.This is a rewarding role where you will be able to draw a clear connection between your work and how it improves the experience of millions of Amazon customers across the globe every day. You will propose and explore publication-worthy innovation in NLP and IR to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.Your responsibilities include:· Analyze the data and metrics resulting from traffic into Amazon's product search service· Design, build, and deploy effective and innovative ML solutions to improve various components of the search stack, such as indexing, ranking, and query understanding· Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production· Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IRYour benefits include:· Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers· The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems· Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals· Excellent opportunities, and ample support, for career growth, development, and mentorship· Competitive compensation, including relocation support (for both domestic and international candidates)
US, WA, Seattle
Business/Team IntroductionThe Supply Chain Optimization Technologies (SCOT) team builds technology to automate and optimize Amazon’s supply chain of physical goods. We seek a Data Scientist with strong analytical and communication skills to join our team. SCOT manages Amazon's inventory under uncertainty of demand, pricing, promotions, supply, vendor lead times, and product life cycle. We optimize complex trade-offs between customer experience, inventory costs, fulfillment costs, fulfillment center capacity, etc. We develop sophisticated algorithms that involve learning from large amounts of data such as prices, promotions, similar products, and other data from our product catalog in order to automatically act on millions of dollars’ worth of inventory weekly and establish plans for tens of thousands of employees. As a Data Scientist, you will contribute to the research community, by working with other scientists across Amazon and our Supply Chain, as well as collaborating with academic researchers and publishing papers. SCOT also engages in cutting edge research that we try to share with the community. Recent work from SCOT includes papers presented at the NIPS 2017 Time Series Workshop, SSRN, KDD 2018 Time Series Workshop, and ICML 2018 Deep Generative Models Workshop.Data Scientist ResponsibilitiesAs a Data Scientist in SCOT, will be tasked to understand and work with bleeding edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.Major responsibilities include:· Analysis of large amounts of data from different parts of the supply chain and their associated business functions· Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models· Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them· Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations· Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
US, WA, Seattle
Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s human capital and talent programs and processes.People Science Team within GTM is a growing start-up team with direct impact on Amazonians across all of our businesses and locations around the world. We play a crucial role in ensuring top notch data products and insights facilitate our growth and development of talent in intelligent and curious ways. We regularly use data to pitch ideas and drive conversations with Amazon’s Senior Vice President of HR and other executives about how to improve existing talent programs to solve organizational problems focused on (but not limited to) talent differentiation, talent movement, employee-role matching, product integration, promotion practices, organization design and succession planning, and diversity and inclusion, or invent new ones that address the evolving needs of our diverse employee base.We are looking for a self-driven Economist to help shape analytics and research roadmap and enable data-driven innovation that fuel our rapidly scaling talent management mission. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at GTM will be expected to develop new techniques to process large data sets, apply a causal lens to the framework, address ambiguous business problems, and contribute to design of automated systems around the company.You will partner closely with product and program owners, as well as scientists and engineers from other disciplines (e.g. data science, software engineers, data engineering) with a clear path to business impact. You develop innovative and even frighteningly bold plans and ideas to discover new ways to advance our goals. You will be expected to be a thought leader as we chart new courses with our rapidly growing employee populations, and lead the way in experimenting new ideas that have not yet been explored.Key Responsibilities:· Participate in scoping and planning of GTM’s Science roadmap· Uncover drivers, impacts, and key influences on talent outcomes· Build new econometric models to improve existing talent products or those that make the case for new products· Bring a causal lens to questions in human resources employing either experiments or non-experimental approaches· Develop predictive and optimization models for key applications· Navigate a variety of data sources, such as enterprise data, customize surveys, focus groups, and/or external data sources· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives· Work in expert cross-functional teams delivering on demanding projects
US, CA, Virtual Location - California
Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.Economists at Amazon will be expected to work directly with senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company.
US, WA, Seattle
The AWS Central Economics team is looking for a PhD economist. The ideal candidate will have experience with time-series forecasting.You will learn about cloud products, including compute, storage, and databases. You will work on analytic projects requested by senior leadership. You will get the opportunity to learn new techniques. You will be a part of a team with many experienced economists.
US, VA, Arlington
Amazon’s Talent Assessment team designs and implements groundbreaking hiring solutions for one of the world’s fastest growing companies. We work in a fast-paced, global environment where we must solve complex problems (ranging from research-based to technical) and deliver solutions that have impact.We are seeking personnel selection researchers with a strong foundation in the development of pre-hire selection assessments, traditional and alternative legally defensible assessment validation approaches, research methodology, and data analysis. We are looking for equal parts researchers and consultant/thought leaders who are highly adaptable and continual learners who thrive in a fast paced environment.You will work closely with global teams to design and experiment new hiring solutions that predict success for highly complex roles (technical and non-technical) that have great impact on Amazon globally.What you’ll do:· Lead the tactical development and execution of large scale, highly visible personnel selection research projects· Develop and iterate on experimental research studies to optimize qualitative and quantitative hiring strategies· · Develop and innovate on new pre-hire test assessment design, validation, and implementation· · Partner with internal and external technology teams· Influence executive project sponsors and multiple business and development teams across the company· Drive effective teamwork, communication, and collaboration across multiple stakeholder groups
US, VA, Arlington
Amazon’s Talent Assessment team designs, implements, and optimizes hiring systems for one of the world’s fastest growing companies. We work in a data-focused, global environment solving complex problems with deep thought, large-sample research, and advanced quantitative methods to deliver practical solutions that make all aspects of hiring more fair, accurate, and efficient.We're looking for a curious data scientist interested in working on a multi-disciplinary team of applied scientists, psychologists, data engineers, business analysts, and program managers. In this role, you will apply your modeling skills to bust myths, create insights, and produce recommendations to help Amazon evaluate millions of potential new hires per year. You'll be involved in all phases of research and experiment design and analysis, including defining research questions, designing experiments, identifying data requirements, conducting statistical or machine learning-based modeling, and communicating insights and recommendations. You'll also be expected to continuously learn new systems, tools, and industry best practices to analyze big data and enhance our analytics.