Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Differentiating by data science

Eric Colson (Stitch Fix)
11:20am12:00pm Wednesday, September 27, 2017
Data-driven business management, Machine Learning & Data Science
Location: 1A 06/07 Level: Intermediate
Average rating: ****.
(4.67, 3 ratings)

Who is this presentation for?

  • Chief data scientists and VPs and directors of data science

Prerequisite knowledge

  • Experience leading data science teams

What you'll learn

  • Understand how to organize for data science when it is part of the company's strategic differentiation


Companies employ various means of differentiation in order to gain a competitive advantage in the market. Traditional differentiators include network economies, branding, economies of scale, and so on. But the availability of data and compute resources, combined with the emergence of new business models, have enable data science to become a strategic differentiator for some companies.

Eric Colson explores what it means to differentiate by data science and explains why companies must now think very differently about the role and placement of data science in the organization. If data science is going to be part of your competitive strategy, it warrants rethinking how the company is organized, how it defines its roles, and how it attracts and retains top talent.

Topics include:

  • Where the data science team should live within the organization
  • Why data science is different from other departments like engineering, finance, or marketing
  • How to create compelling roles for your data science team
  • How to foster innovation without structured programs
  • Considerations for measuring data science talent
  • The role of the data platform team in enabling your data scientists
Photo of Eric Colson

Eric Colson

Stitch Fix

Eric Colson is chief algorithms officer at Stitch Fix, where he leads a team of 80+ data scientists and is responsible for the multitude of algorithms that are pervasive to nearly every function of the company, from merchandise, inventory, and marketing to forecasting and demand, operations, and the styling recommender system. He’s also an advisor to several big data startups. Previously, Eric was vice president of data science and engineering at Netflix. He holds a BA in economics from SFSU, an MS in information systems from GGU, and an MS in management science and engineering from Stanford.