How to Lead in Data Science

A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples.

In How To Lead in Data Science you will learn:

Best practices for leading projects while balancing complex trade-offs
Specifying, prioritizing, and planning projects from vague requirements
Navigating structural challenges in your organization
Working through project failures with positivity and tenacity
Growing your team with coaching, mentoring, and advising
Crafting technology roadmaps and championing successful projects
Driving diversity, inclusion, and belonging within teams
Architecting a long-term business strategy and data roadmap as an executive
Delivering a data-driven culture and structuring productive data science organizations

How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company’s data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they’ve developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You’ll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas.


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