Frontmatter Roy Keyes, Author of Hiring Data Scientists and Machine Learning Engineers: A Practical Guide
Aug 11, 2021
Roy Keyes, a data scientist and consulting expert, shares his journey from studying physics in Kansas to building successful teams in tech startups. He discusses the challenges of hiring in data science, stressing the importance of clear goals and treating candidates like customers. Roy also tackles the impact of ML in finding product-market fit and explains the nuances of data science versus AI. He talks about his decision to write a practical guide on hiring practices while navigating the challenges of self-publishing during the pandemic.
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From Physics Lab To Data Science Leadership
- Roy Keyes moved from physics and medical physics into data science, then into startups and management.
- He discovered he enjoyed hiring and multiplying impact through high-quality teams.
Computation Is Central To Medical Physics
- Medical physics problems required heavy computational work like Monte Carlo simulations to be clinically useful.
- Roy focused on speeding up those calculations to make particle therapy practical.
Validate ML Before Betting Product Fit
- Use analytics (A/B testing) and ML carefully to test product-market fit rather than assuming AI will solve product problems.
- Validate that ML adds meaningful value and that required data is available and ethical to collect.
