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:
- Learn about the challenges and common mistakes when hiring data scientists.
- Learn the best practices for how top companies hire data scientists.
- Learn how to efficiently hire the best data science candidates.

[BLOG] How to Hire Data Scientists and Data Analysts: [ Ссылка ]

[PODCAST EPISODE] How Data Leaders Can Build an Effective Talent Strategy: [ Ссылка ]

[WEBINAR] How to Build and Recruit World Class Data Teams: [ Ссылка ]

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