Emily Glassberg Sands is Head of Data Science and Data Engineering at Coursera. Her team builds the statistical models and machine learning algorithms that power content discovery and help scale an engaging and personalized learning experience; leads the measurement, experimentation, and inference that informs Coursera's product and business strategy; and develops the analytical products and direct data access for the company’s university partners and enterprise customers. She holds a BA from Princeton and a PhD from Harvard, both in Economics. Her academic research blends experimentation, econometrics, and machine learning to better understand labor markets and consumer decision-making, and has been featured in the popular press including the New York Times, the Wall Street Journal, and National Public Radio.

As the leader of Airbnb’s Data team, Elena is responsible for driving the strategy for how Airbnb uses data for decision making and to infuse products and processes with algorithms.  She started as one of the first data scientists at the company, where her initial work set up frameworks for understanding the impact of company initiatives - from the operations teams to the product teams. Her mission is to create a data-driven culture at the company.

Prior to Airbnb, Elena received a Ph.D. in Education and an M.A. in Economics from Stanford University. Her dissertation used advanced statistical modeling to predict friendships in schools and analyzed how those friendships impacted the likelihood a lower income student enrolled in college. She received the Stanford Interdisciplinary Graduate Fellowship for this work. Originally from New Haven, Connecticut, she received a B.A. from Yale University studying Ethics, Politics, and Economics.

Stephanie leads the Data Science team for Payments at Airbnb. She got hooked into the complexity, the scale and the impact of Payments when she started working at PayPal. She leveraged data to shape the direction of the business at PayPal, Zong, a mobile payment start-up acquired by PayPal, as well as the leading freelancing platform Upwork. She holds a Master of Management from HEC Paris, a leading university in Europe. Mother of three young boys, she is passionate about bringing diversity to the workforce.

Anna is a Data Scientist on the Infrastructure team at Airbnb. She studied Operations Research Financial Engineering at Princeton (BSE), and after a summer as a data science intern she joined Airbnb in 2017. Prior to joining Infrastructure, Anna was a Data Scientist on the People Analytics team. Her current focus is optimization of infrastructure costs such as compute and storage.

Lilei Xu is currently a Data Science Manager on the Growth and Traffic Platform team of Airbnb. She graduated from Harvard Economics Department with a Ph.D. in Industrial Organization and Corporate Finance. She joined Airbnb’s Data Science team in 2015 and transitioned into a Data Science manager in 2017. Her main areas of focus include incrementality measurement system and paid growth bidding optimizations.

Mitra is a data scientist on the Cities team at Airbnb, which has a mission of building tools for cities across the world to achieve sustainable home sharing. Mitra works on understanding the impact of different regulations on Airbnb as well as the impact of Airbnb on communities and cities. Her background in economics provides the opportunity to apply quasi-experimental techniques in the aspects of her work where experimentation is not possible. Mitra received a PhD in economics from Harvard University and a BA in applied mathematics from U.C. Berkeley. In her spare time she obsessively checks, reads, and listens to the news.

Lindsay is a Data Science Tech Lead at Airbnb. She joined Airbnb in 2015 after Insight Data Science, a fellowship that helps academics transition to tech jobs. She has a PhD in Government (Political Science) from Georgetown University. At Airbnb she's worked on Guest Growth, Internationalization, Mobile strategy, Experimentation and is now focused on Host Growth. She is passionate about the power of data to drive strategy and data products to drive business growth, and her favorite algorithm is division.

Tatiana is a data scientist on the Guest team at Airbnb, where she focuses on improving the search experience of our users and advanced experimentation tools. Prior to joining Airbnb, she was an Assistant Professor of Statistics at University of California, Santa Cruz. Tatiana received her PhD in Statistics from Lancaster University and her MSc in Statistics and Operational Research from University of Athens. During her PhD she developed Bayesian methodology based on hidden Markov models to identify potential interactions between zoonoses and improved the efficiency of the Metropolis-adjusted Langevin algorithm.