Best Practices for Hiring Data Scientists

Data science involves disparate skills from statistics to programming to communication. The difficulty of assessing this broad set of technical skills causes pain for both hirers and applicants. Candidates are often asked to answer arcane statistics questions on the spot, or live code solutions to the sort of data structure/algorithm CS problems that even professional programmers resent.

In this webinar, Isaac presents findings from a series of interviews with 20 data science hiring managers at leading organizations across industry (e.g. FAANG, finance, startups). He will discuss common patterns that emerged around both challenges and best practices, and make some actionable recommendations for data science teams looking to improve their hiring processes.

Key Takeaways: