Many managers of data science teams become managers because they were great individual contributors and not necessarily because they have the skills or training to lead a team. (I include myself in that group.) But management is a skill unto itself, and relying on your experience as a successful individual contributor is not enough to ensure that you are able to retain and develop great talent while delivering valuable learnings, products, and outcomes back to the organization. Great data scientists have career options and won’t abide bad managers for very long. If you want to retain great data scientists you’d better commit to being a great manager.
Managing a Data Science Team
Give your team good work and connect it to the business.
October 24, 2018
Summary.
Great data scientists have career options and won’t abide bad managers for very long. If you want to retain great data scientists you need to care about your team members, connect their work to the business, and design a diverse, resilient, high-performing team. The best way to build trust is to make sure your team members have interesting projects to work on and that they’re not overburdened by projects with vague requirements or unrealistic timelines. To get the most from a data scientist’s time, they need to have a clear understanding of what the business goal behind the project is. Finally, as a data science manager, you’ll get lots of applications. Take advantage of that to be picky in the right ways.
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New!
HBR Learning
Digital Intelligence Course
Accelerate your career with Harvard ManageMentor®. HBR Learning’s online leadership training helps you hone your skills with courses like Digital Intelligence . Earn badges to share on LinkedIn and your resume. Access more than 40 courses trusted by Fortune 500 companies.
Excel in a world that's being continually transformed by technology.