Who Is Chenfei Lu From Jeopardy? Meet the Economist and Data Scientist Behind Waymo and Uber Pricing Systems

Chenfei Lu is one of the latest highly accomplished contestants to appear on Jeopardy!, bringing with her an extraordinary professional background that spans economics, machine learning, finance, artificial intelligence, and marketplace optimization. Based in San Francisco, California, Lu has spent years working at the forefront of data science and economic strategy for some of the most influential technology companies in the world.

Currently part of the Data Science division at autonomous vehicle company Waymo, Chenfei has developed expertise in marketplace behavior, pricing systems, experimentation, demand forecasting, and business optimization. Her work combines empirical economics with large-scale machine learning systems, helping companies better understand how consumers, pricing structures, and marketplaces operate in real time.

Before joining Waymo, Lu held senior data science leadership roles at Faire and Uber, where she helped design and optimize complex pricing systems and marketplace infrastructure. Her resume reflects a rare blend of elite academic credentials, high-level economic research, corporate strategy, and technical innovation.

For Jeopardy! viewers, Chenfei Lu stands out as a contestant whose career represents the modern intersection of economics, artificial intelligence, and data-driven decision-making.

Currently Working in Data Science at Waymo

As of 2025, Chenfei Lu works in Data Science at Waymo, Alphabet’s autonomous driving company. Waymo is widely recognized as one of the leading companies developing self-driving vehicle technology, and data science plays a critical role in the company’s operations and long-term strategy.

Her work at Waymo builds naturally on years of experience analyzing marketplace systems, pricing models, incentives, and large-scale consumer behavior. Autonomous transportation companies rely heavily on predictive modeling, optimization systems, experimentation frameworks, and advanced analytics, all areas where Lu has extensive professional experience.

Before joining Waymo, Chenfei spent four years at Faire, an online wholesale marketplace connecting independent retailers and brands. At Faire, she worked as a Staff Data Scientist and Tech Lead, expanding her work into pricing systems, memberships, incentives, search and ranking systems, and shipping cost prediction.

Her responsibilities across these companies highlight a career focused on improving marketplace efficiency and profitability through rigorous economic analysis and machine learning-driven decision-making.

A Major Contributor to Uber’s Pricing and Marketplace Systems

One of the most significant periods of Chenfei Lu’s career came during her more than five years at Uber, where she held increasingly senior data science leadership roles focused on marketplace optimization and pricing strategy.

At Uber, Lu worked extensively on pricing systems, demand forecasting, experimentation, and marketplace balancing. She contributed to areas connected to surge pricing, consumer demand modeling, and pricing strategy for Uber Eats. These systems are essential for balancing supply and demand across large transportation and delivery platforms operating in real time.

Later in her tenure, Chenfei led Uber Eats’ Eater Structural Pricing team. In that role, she combined economics, machine learning, experimentation, and business strategy to optimize pricing structures for consumers and platform participants. Her work helped shape how pricing decisions impacted user behavior, platform profitability, and marketplace stability.

Marketplace optimization at companies like Uber involves extraordinarily complex modeling systems that require expertise in statistics, economics, causal inference, and behavioral analysis. Lu’s leadership in these areas reflects both strong technical skills and a sophisticated understanding of platform economics.

Her experience at Uber established her as a specialist in large-scale marketplace systems and economic optimization within the technology sector.

Strong Academic Foundations in Economics and Finance

Before entering the technology industry, Chenfei Lu built an exceptional academic and research background rooted in economics, mathematics, and finance.

She graduated summa cum laude from Northwestern University with a Bachelor of Arts degree in Economics and Mathematics. She also earned honors in Economics and was elected to Phi Beta Kappa, one of the nation’s most prestigious academic honor societies.

After Northwestern, Lu continued her studies at the University of Chicago Booth School of Business, where she earned both an MBA and a Ph.D. in Finance. The University of Chicago has long been considered one of the world’s most influential institutions in economics and finance, particularly known for quantitative analysis, market theory, and empirical research.

Her doctoral studies focused on corporate finance, industrial organization, housing markets, mortgage markets, and applied microeconomics. Much of her research examined financial distress during the Great Recession, including how lender incentives affected delinquent mortgage resolutions and how investor activity influenced housing markets.

This research combined theoretical economics with real-world financial systems and policy implications, laying the groundwork for the applied economic work that later defined her professional career.

Experience in Investment Banking, Government, and Economic Policy

Prior to her transition into technology and advanced data science, Chenfei Lu gained valuable experience across finance, government, and public policy institutions.

She worked in mergers and acquisitions investment banking at Lazard Freres & Co., one of the world’s most respected financial advisory firms. M&A banking requires advanced financial modeling, valuation analysis, and strategic corporate assessment, providing Lu with strong early exposure to high-level finance.

Her background also includes serving as an Associate Economist at the Federal Reserve Bank of Chicago, where she gained experience in economic analysis and research connected to monetary policy and financial systems.

Additionally, Lu held roles at Morningstar and the U.S. Department of State. These positions exposed her to investment analysis, public policy, and international economic systems early in her career.

Together, these experiences demonstrate the remarkable breadth of her professional background. Before becoming a leader in marketplace optimization and applied data science, she had already developed expertise spanning finance, economics, government, and policy analysis.

Researching Housing Markets and the Great Recession

A major component of Chenfei Lu’s academic work focused on understanding housing markets and financial distress during the Great Recession.

Her research examined how lender incentives influenced mortgage resolution outcomes and how financial distress affected housing market behavior. She also explored how investor participation impacted housing markets during periods of economic instability.

These areas of research sit at the intersection of corporate finance, industrial organization, public policy, and applied microeconomics. Such work often involves advanced econometric modeling, large-scale datasets, and sophisticated statistical analysis.

Her studies contributed to broader conversations surrounding housing affordability, financial regulation, foreclosure systems, and market recovery following economic crises.

This background highlights Lu’s longstanding interest in how economic systems affect people’s lives, particularly during periods of financial instability and structural change.

Using AI to Improve Public Communication and Accessibility

Beyond her corporate and economic work, Chenfei Lu has also demonstrated a strong interest in accessibility, public communication, and artificial intelligence tools designed for social impact.

During an AI residency at Propel, she developed a plain language auditing tool intended to improve government communication. The tool uses large language model structured outputs to evaluate whether documents meet readability and accessibility standards based on federal plain language guidelines.

Her public writing on the project reflects concern about how difficult and overly technical government communication can negatively impact individuals relying on public assistance programs, particularly those facing language barriers or complicated legal terminology.

This project highlights a broader dimension of Lu’s professional interests. While much of her career has focused on pricing systems and marketplace optimization, she also appears interested in how AI and technology can improve accessibility and communication for ordinary people.

The work demonstrates a combination of technical expertise and public-minded problem solving that extends beyond traditional business applications.

An Extensive Technical and Analytical Skill Set

Chenfei Lu’s professional profile reflects deep expertise in both economics and modern data science methodologies.

Her technical skill set includes causal inference, optimization, machine learning, experimentation, statistics, financial analysis, corporate finance, data modeling, and marketplace analytics. These skills are central to the modern technology industry, especially within companies relying on large-scale behavioral and pricing systems.

She also specializes in experimentation frameworks and incentive systems, which help companies evaluate how users respond to changes in pricing, rankings, recommendations, and platform structures.

The combination of economics training with machine learning and large-scale data analysis places Lu among a growing generation of economists who work directly inside technology and AI-driven industries rather than traditional academic settings alone.

Her ability to move fluidly between economic theory, public policy, finance, and applied machine learning reflects a highly interdisciplinary and technically advanced career.

Why Chenfei Lu Could Be a Memorable Jeopardy! Contestant

Jeopardy! contestants often stand out when they bring both intellectual depth and diverse professional experience to the game, and Chenfei Lu fits that profile exceptionally well. Her background spans elite academia, corporate finance, advanced economics, public policy, artificial intelligence, and data science leadership.

Her expertise in mathematics, economics, finance, statistics, technology, and business strategy could make her especially strong across a wide range of Jeopardy! categories. Years spent working in highly analytical and fast-paced environments likely contribute to strong problem-solving abilities and quick recall under pressure.

At the same time, her work improving accessibility through AI tools reflects broader intellectual interests extending beyond corporate optimization and marketplace systems.

Although little public information exists regarding her personal relationships or family life, Chenfei Lu’s career achievements already paint the picture of a highly driven and remarkably accomplished professional. Her appearance on Jeopardy! introduces viewers to a contestant whose work sits at the center of economics, machine learning, and the future of data-driven technology.