April 
12
, 
2018
WiDS @ Airbnb

9:00am–11:00am

Subject

Airbnb University Orientation starts at 9:00am. You will have a chance to explore our state of the art campus and meet with fellow peers.

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00:00 AM

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2:00 PM

Opening Credits & Welcome Coffee

Enjoy a fresh cup of coffee before the presentations. We’ll be handing out pamphlets that outline this evening’s details.

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WOMEN IN DATA SCIENCE

Mar 
06
, 
2019
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WiDS @ Airbnb
6:00pm
-
8:30pm

The Women in Data Science (WiDS) Conference aims to inspire and educate data scientists, regardless of gender, and support women in the field. This one-day technical conference provides an opportunity to hear about the latest data science-related research in a number of domains, learn how leading-edge companies are leveraging data science for success, and connect with potential mentors, collaborators, and others in the field.


Join us after the conference to meet Data Scientists from all over the Bay Area! We’ll start the night with dinner and drinks, and then hear from a great lineup of speakers!


An RSVP is required to attend. You will receive a confirmation email if you register correctly. All proceeds, less fees, will be donated to Women who Code, who works in many functions to inspire women to excel in technology careers.


Please note that you must be 21+ to attend, and will need a government issued ID.


Thank you, and we look forward to hosting you!


Agenda

6:00pm

Check-in & mEET SOMEONE NEW

Enjoy dinner and drinks while getting to know other attendees from the conference. 

7:00pm

Welcome 

Guests and Partners, and review the night's lineup. 


7:05 pm

 kEYNOTE Speaker, eMILY GLASSBERG sANDS

Data Science to Power Learning at Scale 


7:30pm 

Q&A with Emily, hosted by Elena gREWAL

We will also be taking questions from the audience, so have them ready!

8:00pm

"OWNING THE ADVENTURE"

A panel discussion with women from our Data Science team. 

The rundown

5:30 PM

Arrive

Sign in, grab a cocktail, and help yourself to snacks.

5:45 PM

Rakia Johnson

The State of Recruiting and intersectionality in Tech

6:00 PM

Adam Neumann

Building and executing upon your ideal canidate profile

6:15 PM

Rebekah Neumann

How Company Culture affects recruiting and retention

WiDS @ Airbnb
September 
12
, 
2019
6:00pm
 – 
9:00pm

The Women in Data Science (WiDS) Conference aims to inspire and educate data scientists, regardless of gender, and support women in the field. This one-day technical conference provides an opportunity to hear about the latest data science-related research in a number of domains, learn how leading-edge companies are leveraging data science for success, and connect with potential mentors, collaborators, and others in the field.


Join us after the conference to meet Data Scientists from all over the Bay Area! We’ll start the night with dinner and drinks, and then hear from a great lineup of speakers!


An RSVP is required to attend. You will receive a confirmation email if you register correctly. All proceeds, less fees, will be donated to Women who Code, who works in many functions to inspire women to excel in technology careers.


Please note that you must be 21+ to attend, and will need a government issued ID.


Thank you, and we look forward to hosting you!


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Speakers + Panelists

Emily GlassbergSands

Head of Data Science and Data Engineering @Coursera

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.

Elena Grewal 

 Director, Head of Data Science @Airbnb 

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 Gabaix

Data Science Manager @Airbnb

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 Matlin 

Data Scientist @Airbnb 

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

Data Science Manager @Airbnb 

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 Akhtari

Data Scientist @Airbnb

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 Pettingill

Data Science Tech Lead @Airbnb

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 Xifara

Data Scientist @Airbnb 

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.

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Agenda

10:00am–12:00pm

Learn

Morning sessions, passive programming, and educational demonstrations

12:00pm–2:00pm

Eat

Buffet-style lunch and refreshments served during presentations on Airbnb for Work

2:00pm–6:00pm

Engage

Afternoon sessions, hands-on workshops, and a full product demo

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Data Science 

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