Pai-Ling Yin, senior manager of research science, is seen speaking to a classroom, there is a chalkboard behind her and she is gesturing with her hands.
Pai-Ling Yin, senior manager of research science, says the highlight of her job is organizing teams of experts across operations, engineering, economics, and data science to answer research questions.
Courtesy of Pai-Ling Yin

Pai-Ling Yin brings an academic’s lens to the study of buying and selling at Amazon

How her background helps her manage a team charged with assisting internal partners to answer questions about the economic impacts of their decisions.

Online bidding services were disrupting the auction industry when Pai-Ling Yin started pursuing her PhD in economics in 1997 at Stanford University. She seized on the data that these services generate to study and understand the new economy emerging from this industry in transition.

“The internet accelerates and scales up transactions,” said Yin. “All these auctions were happening online. I could watch what was happening. ‘Who is going to succeed? Who is going to fail? How is it going to shape the future?’”

These questions led Yin to a PhD thesis on the economics of online auctions for personal computers. They also framed her two decades in academia, where she researched and taught technology strategy, innovation, and entrepreneurship at Harvard Business School, the Massachusetts Institute of Technology (MIT) Sloan School of Management, Stanford’s Department of Economics, and the University of Southern California’s Marshall School of Business.

We are trying to think about, ‘What is the long-term value of any action we take? How do we make sure that we’re giving our customers the best experience?'
Pai-Ling Yin

In 2021, her former advisor at Stanford, Pat Bajari, who is now chief economist and vice president of the Core AI team at Amazon, recruited her to join his team as a senior manager of research science. Core AI uses economics, statistics, and machine learning to understand and design the complex economy of Amazon buyers and sellers.

Today Yin manages a team of economists, program managers, and engineers tasked with helping internal partners across Amazon research questions about the economic impacts of their decisions.

“We are trying to think about, ‘What is the long-term value of any action we take? How do we make sure that we’re giving our customers the best experience? Of the many options we have to interact with customers, which seem to delight them the most?’” Yin explained.

Economics at Amazon
Tatevik Sekhposyan, Amazon Scholar and Texas A&M University professor, enjoys the flexibility of economics and how embracing uncertainty can enhance prediction.

For example, the team works with Amazon’s concessions department to model the best way to respond when a customer returns a product. There are a number of options; each has costs and benefits. Which one best assists customers shopping in the Amazon Store?

The highlight of the job, Yin said, is organizing teams of experts across disciplines such as operations, engineering, economics, and data science to answer these types of questions.

“We’re bringing the best of the best in all these different fields. Many are not my area of expertise. I’m learning every day and engaged in interesting discussions,” she said.

A lifelong learner

Yin, whose parents immigrated to the US from China via Taiwan, is the first US-born member of her immediate family. She completed undergraduate studies at Indiana University in Bloomington on a scholarship from the Wells Scholars Program and earned simultaneous degrees in economics, French, and mathematics, graduating summa cum laude in each.

During her junior year, she was selected as a Truman Scholar, which allowed her to pursue a master’s degree in regulation at the London School of Economics and Political Science. After her time in London, she went to Stanford and met Bajari.

“At the time, the internet was fairly new,” Yin said. “Online businesses had just started, and I was interested in all these new industries.”

Yin was at the forefront of a trend where trained economists end up teaching at business schools.

Her academic research and teaching career focused on the type of industrial organization (i.e., the structure of players in an industry) that emerges from innovation in technology, which can change the structure by changing the cost of entry and transactions in that industry.

Academics at Amazon
The Johns Hopkins business school professor and Amazon Scholar focuses on enhancing customer experiences.

“Any new innovation is going to create this new way of economic actors interacting,” Yin said of the industrial organization concept. “What players emerge? What new technologies are spawned from the original technology? How do industries now interact? How do buyers and sellers interact?"

While teaching technology strategy at MIT, Yin noticed an industrial organization emerging around mobile phones and apps following the introduction of the smartphone in 2007. The moment had echoes of the early days of online auctions. She was intrigued and began to study the mobile app economy from her office in Cambridge.

“The beginning of that whole industry was literally in South San Francisco, not even in the Bay Area,” she said. “All these little startups were finding these little, little offices and doing their things. And I really wanted to be out closer to the action.”

That desire to be at the center of the emerging mobile-computing industry led her back to Stanford, where she co-founded the Mobile Innovation Group with another of her former advisors, economist Tim Bresnahan. Yin’s research focused on entrepreneurship in the mobile-app industry as it emerged and evolved with competing mobile services.

This line of research led to a greater focus on entrepreneurship, which she taught at USC from 2016 until she started at Amazon.

Academics at Amazon
Co-mingling industry experience and academic teaching.

While at USC, Yin co-created a required course for the MBA program on critical thinking. The curriculum is centered on helping students deal with ambiguity — how to make progress in the face of uncertainty. Her former students who are now at Amazon tell her that they regularly apply lessons learned from the course, such as taking a few minutes to ask one more question about a problem to advance their thinking.

“That was the spirit of the class,” she said. “What are these little tools that you might think of as small interventions, which are not going to get to optimum thinking but are going to get to better thinking? Then, as you practice those skills, you’ll get faster and better and, over time, develop that muscle.”

“As a teacher, Pai-Ling empowered her students to think outside the box — each answer begets a new question, and great solutions often come by probing wider and deeper,” said Darren Setiawan, a senior product manager at Amazon who was Yin’s student, teaching assistant, and research assistant at USC. “I was especially fond of her courses and often refer back to her frameworks when dealing with complex work — and life — decisions.”

Practice what you teach

When COVID-19 hit, Yin had been in academia for nearly two decades and was ready for a change. The opportunity to join Amazon brought with it a chance to put into practice her years of training as an economist and research scientist. For example, she brings short- and long-term thinking to the problems her team is asked to solve.

“In the short run, the problem is, what’s the cost-benefit analysis of the issue we’re facing now? But the world is dynamic and changing. You know that analysis has to be redone in a few years. How do we think about anticipating flexibility in the models that we’re creating?” she explained.

Economists at Amazon
How the Amazon Supply Chain Optimization Technologies principal economist uses his expertise in time series econometrics to forecast aggregate demand.

The teacher in her also embraces ambiguity and looks forward to the next big problem that her team gets to solve, whatever it is.

“That’s the exciting part,” she said.

Solving that problem, she noted, will require collaboration among people with a diverse set of expertise — economists, data scientists, psychologists, engineers, and program managers. That’s why she recommends that young scientists learn to appreciate the world through multiple lenses: the lenses of their specific areas of expertise as well as the lenses of their coworkers and colleagues.

“You have expertise, and that is wonderful,” she said, as if speaking to a group of newly minted PhDs. “But it is now your job to figure out where you can contribute and where you are going to learn from others. That approach will contribute to a richer life in both social and problem-solving ways.”

Research areas

Related content

GB, London
Our team's mission is to improve Shopping experience for customers interacting with Amazon devices via voice. We work with Alexa and multiple other teams to research and develop advanced state-of-the-art speech technologies. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history. Key job responsibilities We are looking for a passionate, talented, and inventive Senior Applied Scientist with a background in Machine Learning to help build industry-leading Speech and Language technology. As a Senior Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis. Position Responsibilities: * Participate in the design, development, evaluation, deployment and updating of data-driven models for Speech and Language applications. * Participate in research activities including the application and evaluation of Speech and Language techniques for novel applications. * Research and implement novel ML and statistical approaches to add value to the business. * Mentor junior engineers and scientists. We are open to hiring candidates to work out of one of the following locations: London, GBR
ES, M, Madrid
Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site. The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content? Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. We are open to hiring candidates to work out of one of the following locations: Madrid, M, ESP
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! Our Prime Air Drone Vehicle Design and Test team within Flight Sciences is looking for an outstanding engineer to help us rapidly configure, design, analyze, prototype, and test innovative drone vehicles. You’ll be responsible for developing, improving, and maintaining a suite of multi-disciplinary optimization (MDO) tools across all aircraft design disciplines. You’ll use these to explore new and novel drone vehicle conceptual designs in both focused and wide open design spaces, with the ultimate goal of meeting our customer requirements. You’ll have the opportunity to prototype vehicle designs and support wind tunnel and other testing of vehicle designs. You will directly support the Office of the Chief Program Engineer, and work closely across all vehicle subsystem teams to ensure integrated designs that meet performance, reliability, operability, manufacturing, and cost requirements. In addition, you’ll own the Flight Sciences assessments and analysis methods for the drone vehicle design as it progresses through later stages of development. About the team Our Flight Sciences Vehicle Design & Test organization includes teams that span the following disciplines: Aerodynamics, Performance, Stability & Control, Configuration & Spatial Integration, Loads, Structures, Mass Properties, Multi-disciplinary Optimization (MDO), Wind Tunnel Testing, Noise Testing, Flight Test Instrumentation, and Rapid Prototyping. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, MA, Boston
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Knowledge of applied econometrics is necessary, and experience with SQL and Python would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will build data sets and perform applied econometric analysis, collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Boston, MA, USA | Seattle, WA, USA
ES, M, Madrid
Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site. The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content? Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. We are open to hiring candidates to work out of one of the following locations: Madrid, M, ESP
US, WA, Bellevue
Amazon’s Modeling and Optimization Team (MOP) is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and planning the most complex supply chain in the world. The team is responsible for optimizing the global supply chain for Amazon.com and ensuring that the company is able to inbound goods from seller and vendors, transport them to their target fulfillment center, and deliver to our customers as quickly, accurately, and cost effectively as possible. We work on problems ranging from network design to inventory management, in order to support strategic decisions. It is a terrific opportunity to have a direct impact in the business while pushing the boundaries of science. Key job responsibilities We are seeking an experienced scientist who has solid background in Operations Research, Operations Management, Applied Mathematics or other similar domain. In this role, you will develop models and solution algorithms that are innovative and scalable to solve new challenges in the inventory management space. You will collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission. You have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies. You will also work with engineering teams to identify new data requirements, deploy new models or simplifying existing processes. About the team https://www.aboutamazon.com/news/innovation-at-amazon/how-artificial-intelligence-helps-amazon-deliver We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, CA, Santa Clara
Do you wish to create the greatest possible worldwide impact in healthcare? We, at Amazon Health Store Tech, are working towards the best-in-class healthcare storefront to make high-quality healthcare reliable, accessible, and intuitive. Our mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. We are looking to hire and develop subject-matter experts in AI who focus on data analytics, machine learning (ML), natural language understanding (NLP), and deep learning for healthcare. We target high-impact algorithmic unlocks in areas such as natural language understanding (NLU), Foundation Models, Large Language Models (LLMs), document understanding, and knowledge representation systems—all of which are of high-value to our healthcare products and services. If you are a seasoned, hands-on Principal Applied Scientist with a track record of delivering to timelines with high quality, deeply technical and innovative, we want to talk to you. You will bring AI and machine learning advancements to real-time analytics for customer-facing solutions in healthcare. You will explore, innovate, and deliver advanced ML-based technologies that involve clinical and medical data. You are a domain expert in one or more of the following areas: natural language processing and understanding (language models, transformers like BERT, GPT-3, T-5, etc.), Foundation Models and LLMs, deep learning, active learning, reinforcement learning, and bioinformatics. Key job responsibilities As an Principal Applied Scientist, you will take on challenging and ambiguous customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and medical research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to its implementation. A successful candidate has excellent technical depth, scientific vision, great implementation skills, and a drive to achieve results in a collaborative team environment. You should enjoy the process of solving real-world, open-ended problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a fearless disruptor, prolific innovator, and a reputed problem solver—someone who truly enables machine learning and statistics to truly impact the lives and health of millions of customers. You mentor and help develop a team of Applied Scientists and SDEs and work with key leaders to guide this top talent to push the boundary of science and next generation of product. They will lead the technical implementation of our evidence-based retrieval sub-system that ingests, indexes and retrieves relevant data in different forms and from multiple sources given the customer question and context. We are open to hiring candidates to work out of one of the following locations: Santa Clara, CA, USA | Seattle, WA, USA
US, WA, Bellevue
Imagine being part of an agile team where your ideas have the potential to reach millions of customers. Picture working on cutting-edge, customer-facing solutions, where every team member is a critical voice in the decision making process. Envision being able to leverage the resources of a Fortune 500 company within the atmosphere of a start-up. Welcome to Amazon’s NCRC team. We solve complex problems in an ambiguous space, focusing on reducing return costs and improving the customer experience. We build solutions that are distributed on a large scale, positively impacting experiences for our customers and sellers. Come innovate with the NCRC team! The Net Cost of Refunds and Concessions (NCRC) team is looking for a Senior Manager Data Science to lead a team of economists, business intelligence engineers and business analysts who investigate business problems, develop insights and build models & algorithms that predict and quantify new opportunity. The team instigates and productionalizes nascent solutions around four pillars: outbound defects, inbound defects, yield optimization and returns reduction. These four pillars interact, resulting in impacts to our overall return rate, associated costs, and customer satisfaction. You may have seen some downstream impacts of our work including Amazon.com customer satisfaction badges on the website and app, new returns drop off optionality, and faster refunds for low cost items. In this role, you will set the science vision and direction for the team, collaborating with internal stakeholders across our returns and re-commerce teams to scale and advance science solutions. This role is based in Bellevue, WA Key job responsibilities * Single threaded leader responsible for setting and driving science strategy for the organization. * Lead and provide coaching to a team of Scientists, Economists, Business Intelligence Engineers and Business Analysts. * Partner with Engineering, Product and Machine Learning leaders to deliver insights and recommendations across NCRC initiatives. * Lead research and development of models and science products powering return cost reduction. * Educate and evangelize across internal teams on analytics, insights and measurement by writing whitepapers, knowledge documentation and delivering learning sessions. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, WA, Bellevue
We are designing the future. If you are in quest of an iterative fast-paced environment, where you can drive innovation through scientific inquiry, and provide tangible benefit to hundreds of thousands of our associates worldwide, this is your opportunity. Come work on the Amazon Worldwide Fulfillment Design & Engineering Team! We are looking for an experienced and Research Scientist with background in Ergonomics and Industrial Human Factors, someone that is excited to work on complex real-world challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will define human factor / ergonomic thresholds resulting in design and implementation of safe and efficient workspaces and processes for our associates. Your role will entail assessment and design of manual material handling tasks throughout the entire Amazon network. You will identify fundamental questions pertaining to the human capabilities and tolerances in a myriad of work environments, and will initiate and lead studies that will drive decision making on an extreme scale. .You will provide definitive human factors/ ergonomics input and participate in design with every single design group in our network, including Amazon Robotics, Engineering R&D, and Operations Engineering. You will work closely with our Worldwide Health and Safety organization to gain feedback on designs and work tenaciously to continuously improve our associate’s experience. Key job responsibilities - Collaborating and designing work processes and workspaces that adhere to human factors / ergonomics standards worldwide. - Producing comprehensive and assessments of workstations and processes covering biomechanical, physiological, and psychophysical demands. - Effectively communicate your design rationale to multiple engineering and operations entities. - Identifying gaps in current human factors standards and guidelines, and lead comprehensive studies to redefine “industry best practices” based on solid scientific foundations. - Continuously strive to gain in-depth knowledge of your profession, as well as branch out to learn about intersecting fields, such as robotics and mechatronics. - Travelling to our various sites to perform thorough assessments and gain in-depth operational feedback, approximately 25%-50% of the time. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA