So you’ve decided that your organization needs data scientists (whether to determine which metrics to optimize for, to employ data to suggest new innovations or addressable markets, or to develop machine-learning models and implement predictive analytics). You’ve created scaleable infrastructure and distributed systems to process data. You’ve figured out who to hire and how. Now, what do you do with them?
Yael Garten offers examples of how companies like LinkedIn use data to make business decisions, and describes the process, culture and tools needed to run a data driven organization. Yael reviews the spectrum of data science used within an organization and explores organizational needs, such as the democratization of data via self-serve data platforms for experimentation, monitoring, and data exploration, as well as the challenges that come with such systems. Yael covers important foundations such as data quality and tracking and merging disparate data sources. Yael also presents examples of how data scientists can promote the art, science, and politics of defining which performance measurement metrics should be used to drive the business.
Participants will leave this session with the ability to identify opportunities for data scientists to contribute within their organization and with an understanding of what investments are needed to drive transformation into a data-driven organization.
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.
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