Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA
Yael Garten

Yael Garten
Director, Data Science, LinkedIn

Website

Yael Garten is director of data science at LinkedIn, where she leads a team that focuses on understanding and increasing growth and engagement of LinkedIn’s 400 million members across mobile and desktop consumer products. Yael is an expert at converting data into actionable product and business insights that impact strategy. Her team partners with product, engineering, design, and marketing to optimize the LinkedIn user experience, creating powerful data-driven products to help LinkedIn’s members be productive and successful. Yael champions data quality at LinkedIn; she has devised organizational best practices for data quality and developed internal data tools to democratize data within the company. Yael also advises companies on informatics methodologies to transform high-throughput data into insights and is a frequent conference speaker. She holds a PhD in biomedical informatics from the Stanford University School of Medicine, where her research focused on information extraction via natural language processing to understand how human genetic variations impact drug response, and an MSc from the Weizmann Institute of Science in Israel.

Sessions

10:00am–10:30am Tuesday, 03/29/2016
Data 101

Location: LL20B
Yael Garten (LinkedIn)
Average rating: ***..
(3.50, 2 ratings)
You’ve decided you need data scientists. You know who to hire. Now, what do you do with them? Yael Garten offers examples of how companies like LinkedIn use data to make business and product decisions. Yael reviews the spectrum of data science, and discusses the culture, process and tools needed to transform companies into data-driven organizations. Read more.
5:10pm–5:50pm Wednesday, 03/30/2016
Moderated by:
Michael Dauber (Amplify Partners)
Panelists:
Yael Garten (LinkedIn), Monica Rogati (Data Natives), Daniel Tunkelang (Various)
Average rating: ****.
(4.14, 7 ratings)
We’ve all heard that rare breed the data scientist described as a unicorn. In building your DS team, should you hold out for that unicorn or create groups of specialists who can work together? Michael Dauber, Yael Garten, Monica Rogati, and Daniel Tunkelang discuss the pros and cons of various team models to help you decide what works best for your particular situation and organization. Read more.