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Building Data Science Teams

Video Description

Imagine cooking a stew with a single ingredient or growing a country garden with a single type of flower. One-dimensional efforts like these yield bland and boring results. Now imagine staffing a data science team with only PhDs in machine learning. In spite of the impressive pedigree, the result would be similar: bland, boring, and, possibly worse, ineffective.

But if not just data people, then who?

Data scientist Paco Nathan answers that question and more in this video on how to build a data science team. Cited in 2015 as one of the "Top 30 People in Big Data and Analytics" by Innovation Enterprise, Nathan offers insider tips gleaned from his 30+ years in technology.

  • Assess the need for a data science team: Advantages, disadvantages, and how big should it be?
  • Identify internal corporate sponsors to get buy-in for the data science approach
  • Manage the transition of the data science team into the organization
  • Discover how to identify and hire the right people for the role
  • Learn best practices for setting up, organizing, and managing the team
  • Practice cultivating the team and their professional growth
  • Perform team gap analysis and workflow analysis
  • Absorb invaluable Dos and Don’ts