Corporate Data Science – Angela Bassa

Presenter: Angela Bassa, Director of Data Science at iRobot
Title: Corporate Data Science
Level: All, Beginner, Intermediate, Advanced,
Type: Premium Training, Non-technical
Length: 47 minutes

Overview: In this talk, Angela Bassa discusses strategies of building and maintaining successful data science teams in a corporate setting. Bassa focuses on common mistakes and errors that companies making when setting out to build data science teams

Learning outcomes:

• Teach how to deliver creative and novel solutions.
• Dispel myths such as “Unicorns” and “Super-chickens” that hurt companies and their data science teams.
• Help those working in the industry who want to achieve a better ROI from data science, especially those in charge of hiring data professionals.

Talk Timeline

Introduction and Overview 0:00 – 2:00

Data Science-ing In Industry 2:47 – 11:14 

• The commercial spectrum
• Bespoke questions <-> Production software
• Where does data science fit?
• Pigeonholing Unicorns
• Blended Objectives

Building Effective Data Science Teams 11:14 – 26:36 

• Unicorns Don’t Really Exist. You want to have a well balanced team.
• Dynasties and Intellectual Inbreeding
• Mirror-tocracies & Survivorship Bias
• Building a Large Reality
• There’s More Than One Way to Skin a Cat
• Mistakes Might Have Been Made
• Common Blind Spots
• Multiple-Objective Decision Analysis
• How To Interview For The Best Intersections

Proper Care and Maintenance of Data Teams 26:36 – 37:47 

• You Have an Awesome Team in Place, Now What?!
• Data Team’s Responsibilities
• Why Do You Have To Care?
• “Any sufficiently advanced negligence is indistinguishable from malice.” – Deb Chachra
• It’s Not That No One Cares
• When Should You Start
• What You Expect
• What Actually Exists: A System Optimized For Not-Analysis
• How to Care
• Documentation is How You “Program” A Business
• What Should You Document
• What Will You Want to Know About the Data?
• Having Junior Team Members is a Great Forcing Function!

Q&A Portion 37:47 – 47:08 

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