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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Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The ML team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As an ML Data Scientist in the AWS ML team, you'll partner with technology and business teams to build new services that surprise and delight our customers. You will be working with terabytes of text, images, and other types of data to solve real-world problems.You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will help by developing new ML models, pipelines and architectures to help customers solve their critical business cases, such as autonomous driving, supply chain optimization, predictive maintenance, fraud detection and more. You will support our customers on their ML journey by helping to develop Proof of Concepts, and at the same time helping them understand the technology behind the scientific choices you make.We’re looking for top ML data scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.The primary responsibilities of this role are to:· Use deep learning, machine learning and analytical techniques to create scalable solutions for business problems· Design, development and evaluation of highly innovative models for predictive learning, content ranking, and anomaly detection· Interact with customers directly to understand the business problem, help and aid them in implementation of DL/ML algorithms to solve problems· Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 40%.We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.This team will be comprised of Deep Learning Architects and Data Scientists to create cutting edge solutions for clients across EMEA. We are currently recruiting for talented individuals in the following cities: London and Berlin. Discover more at https://www.amazon.jobs/en/teams/amazonai.
US, WA, Seattle
Interested in driving thought leadership on customers discovering Private Brands? We’re building intelligent data models and NLP algorithms that will transform digital marketing discovery for Private Brands at Amazon. Come join us!We are looking for a senior scientist to lead innovation for our discovery efforts across all placements and all page types by developing innovative algorithms to determine the right content to serve within the right context. This role has a significant global revenue impact. At the heart of our discovery engine are systems for optimizing query sourcing, merchandising allocations, experimentation infrastructure, machine learning methods for inference and metrics-driven closed loop optimizations. This Senior Applied Scientist is responsible for innovation aimed at step-changing these systems, and accelerating the pace of Machine Learning and Optimization. In addition, this scientist will be required to invent new approaches in solving challenging problems like cold start product recommendation, real-time learning customer intent and personalizing contents and optimizing trade-offs between incremental Private Brands sales and the foregone advertising opportunities.To be successful in this role you will need to be comfortable defining a long-term science vision for discovery across placements, and translating that direction into specific plans for applied scientists, as well as engineering and product teams. This is a role that combines science leadership, organizational ability, technical strength, product focus and business understanding. The ideal candidate will be an independent thinker who can make convincing, information-based arguments. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. This person will have sound judgment and help recruit and groom high caliber science talent.
US, WA, Seattle
The Sustainability Science and Innovations (SSI) team is looking for an Applied Scientist to join our team in building customer-focused sustainability products. The SSI team applies Machine Learning, Data Science, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one sustainability solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Sustainable economy, and work closely with scientists and economists. We are particularly interested in candidates with experience building predictive models and working with distributed systems.
IN, KA, Bangalore
Hundreds of millions of customers, billions of transactions, petabytes of data… How to use the world’s richest collection of e-commerce and device usage data to acquire new customers, target existing customers, and predict customer behavior? Amazon’s Consumer Behavior Analytics team seeks a Data Scientist for building analytical solutions that will address increasingly complex business questions.Amazon.com has a culture of data-driven decision-making and demands business intelligence that is timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities.As a Data Scientist in the team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the marketing and product management team through a combination of data mining techniques as well as use statistical and machine learning techniques for segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.Responsibilities· Demonstrate through technical knowledge on Statistical modeling, Probability and Decision theory, Operations Research techniques and other quantitative modeling techniques· Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management· Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area· Innovate by adapting new modeling techniques and procedures· You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets.· You should have exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.· You will extract huge volumes of data from various sources and message streams and construct complex analyses. You will implement data flow solutions that process data real time on message streams from source systems.· You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.· You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training.· Your teams will work with distributed machine learning and statistical algorithms upon a large Hadoop cluster to harness enormous volumes of online data at scale to serve our customers.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The ML team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As a Sr. ML Data Scientist in the AWS ML Solutions Lab team, you'll partner with technology and business teams to build new services that surprise and delight our customers. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will help by developing new ML models, pipelines and architectures to help customers solve their critical business cases, such as autonomous driving, supply chain optimization, predictive maintenance, fraud detection and more. You will support our customers on their ML journey by helping to develop Proof of Concepts, and at the same time helping them understand the technology behind the scientific choices you make.We’re looking for Senior ML Data Scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.The primary responsibilities of this role are to:· Use deep learning, machine learning and analytical techniques to create scalable solutions for business problems· Design, development and evaluation of highly innovative models for predictive learning, content ranking, and anomaly detection· Interact with customers directly to understand the business problem, help and aid them in implementation of DL/ML algorithms to solve problems· Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 40%.We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.This team will be comprised of Deep Learning Architects and Data Scientists to create cutting edge solutions for clients across EMEA. We are currently recruiting for talented individuals in the following cities: London and Berlin. Discover more at https://www.amazon.jobs/en/teams/amazonai.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The ML team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As an ML Data Scientist in the AWS ML team, you'll partner with technology and business teams to build new services that surprise and delight our customers. You will be working with terabytes of text, images, and other types of data to solve real-world problems.You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will help by developing new ML models, pipelines and architectures to help customers solve their critical business cases, such as autonomous driving, supply chain optimization, predictive maintenance, fraud detection and more. You will support our customers on their ML journey by helping to develop Proof of Concepts, and at the same time helping them understand the technology behind the scientific choices you make.We’re looking for top ML data scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.The primary responsibilities of this role are to:· Use deep learning, machine learning and analytical techniques to create scalable solutions for business problems· Design, development and evaluation of highly innovative models for predictive learning, content ranking, and anomaly detection· Interact with customers directly to understand the business problem, help and aid them in implementation of DL/ML algorithms to solve problems· Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes· Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 40%.We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.This team will be comprised of Deep Learning Architects and Data Scientists to create cutting edge solutions for clients across EMEA. We are currently recruiting for talented individuals in the following cities: London and Berlin. Discover more at https://www.amazon.jobs/en/teams/amazonai.
IN, TS, Hyderabad
Are you interested in building the next-generation services that will redefine large scale transportation?We are looking for data scientists to be based in Hyderabad/Bangalore, India with 5+ years of experience in problem-solving using statistical modelling and data science.As part of transportation business, work on creating opportunities to improve network operations for speed and efficiency. As data scientist, you will build forecasting, optimization, outlier detection models to improve predictability and reliability in network operations. Responsibilities include:· Collaborate with operators, program managers, analysts to define right analytical framework and identify improvement opportunitie· Collaborate with engineers, product managers, and analysts to design and implement analytical products· Design, experiment, and scale data driver solutions
US, NY, New York
How can Amazon improve the advertising experience for customers around the world? How can we help advertisers and customers find each other in a meaningful way? Amazon Advertising creates and transforms the connection between retailers, service providers and customers. Join the Analytics & Insights Team to contribute to product and service solutions that allow us to solve this with data science. If you are passionate about developing analytics and testing solutions to solve business problems, and are looking for a team that drives results to help influence Amazon business decisions, this is the right place for you.The Analytics & Insights Professional Services Team is looking for a Head of Advertising Experimentation Team to lead a team of Data Scientists and Business Analysts who analyze big data to build models and algorithms that power our advertising experimentation services and products. We work with advertisers on recommendations for testing in order to improve their advertising effectiveness and strive to better understand the advertising and non-advertising features that best influence and predict advertising campaign performance and incrementality. In this role, you will set the vision and direction for the team and collaborate with internal stakeholders across product and services to scale and advance our experimentation and incrementality testing offerings. The ideal candidate must be willing to effectively lead the team, project-manage and prioritize across multiple stakeholders and tasks, exhibit strong problem-solving skills and be ready to jump into a fast-paced, dynamic and fun environment.Responsibilities:· Lead and provide coaching to the Advertising Experimentation Team including Data Scientists and Business Analysts.· Partner with advertisers and experimentation teams to generate A/B and incrementality test recommendations to improve marketing effectiveness and inform their future marketing investments.· Work with product, data science, experimentation and analytics teams to share knowledge from performance tests, design packaged experimentation insights and inform future product roadmaps.· Use Amazon’s unique data, analyze huge and complex data sets, design and implement solutions using a range of data science methodologies to solve complex business problems.· Demonstrate deep analytical ability, and develop great expertise in Amazon’s proprietary metrics, working to constantly evolve how we analyze and communicate data driven insights to our advertisers.· Build consensus with business stakeholders on how your models and algorithms will drive the optimal results for Amazon customers.· Educate advertisers and internal teams on performance and incrementality testing by writing whitepapers and knowledge documentation and delivering learning sessions.