Building Exceptional Data Science Teams: A Systematic Hiring Framework
Jeremy Stanley, Chief Data Scientist at Sailthru, presents a data-driven hiring methodology for recruiting remarkable data scientists that improves accuracy, reduces candidate loss, increases offer acceptance, and minimizes hiring effort simultaneously. The approach emphasizes designing interview processes that mirror actual job requirements rather than following traditional hiring practices. Stanley shares principles and implementation strategies influenced by leaders like Riley Newman at Airbnb and Drew Conway.
Metrics in this report
80%
goal
percentage of great candidates who should receive offers
3count
minimum
average number of competing offers for strong data science candidates
90%
goal
percentage of hires becoming exceptional employees
10%
maximum
percentage of team time spent on hiring activities
65%
goal
percentage of extended offers that should be accepted
50%
median
current state accuracy for most managers
20%
minimum
current state time spent by hiring team
50%
maximum
current state success rate in competitive data science market