S4: Managing Data Science in the Enterprise

Organizing around data is a concern for the whole business. The myth of the lone ranger data scientist is very much that: effectively leveraging data requires cross-functional collaboration, organizational adaptation, and an organizational understanding of what using data to create business value entails.

In this day-long tutorial, we will share our methods and observations from three years of effectively deploying data science in enterprise organizations. Attendees will learn how to build, run and get the most value from data science teams, and how to work with and plan for the needs of the business.

Agenda

Building the right culture
Organizational concerns for data science
Data science techniques for business
Tools and platforms
Managing and hiring data scientists
Methods for running data science projects
Deploying data science: from the lab to the factory

With over 15 years in advanced analytical applications and architecture, John is dedicated to helping organizations become more data-driven. He combines deep expertise in analytics and data science with business acumen and dynamic engineering leadership.

Jin brings to SVDS over twenty years of experience driving data-fueled partnerships, integrations, business strategies, and analytics across multiple industries including healthcare, e-commerce, media, and software development. She is boundlessly enthusiastic about enabling business with data.

An expert in quantitative modeling, Jeffrey brings over 17 years of experience applying econometric, statistic, and mathematical modeling techniques to real-world challenges. He brings a strong background in finance as well as a passion for leading data science teams in finding innovative solutions to challenging business problems.