Drew Conway, PhD, Founder and CEO at Alluvium, Co-founder of DataKind discusses best practices for building strong data science teams at ODSC East 2018
Key Points:
- Hiring managers and business leaders often overestimate data scientists’ capabilities, resulting in inefficiencies in the hiring process and poor performance from data science teams
- The pre-interview process is crucial. It should involve thoughtful contemplation about the role and why it’s needed, and effective phone screens to ensure that only qualified candidates make it to the interview stage.
- Hiring managers should strive to employ transparency and personability in trying to close a candidate. Good data scientists are likely to have a lot of offers, but if you can show them how they’ll fit in to work they’ll love with their specific strengths and skills, you’ll have a great chance of landing the hire.
In his talk at ODSC East 2018, Dr. Drew Conway, Founder and CEO at Alluvium, described the state of human capital in the world of data science and business and best practices for building a data science company. Across virtually all industries, businesses are beginning to see the potential of data and artificial intelligence to transform how they work. The result is what Conway calls a “Jurassic Park moment” of data science, where companies are working to build teams of ‘unicorn’ data scientists capable of solving their most difficult challenges. The problem is, many hiring managers and business leaders don’t know where to begin when it comes to attracting and retaining top data science talent for their organizations, much less about how to help new data scientists thrive at their companies. Using a series of examples from his own career, as well as hiring practices employed by Alluvium, Conway offers business leaders specific and practical advice to hire top data science teams.
