How to Lead in Data Science

Book Synopsis: IN A WORD A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples."Spot-on as a career resource! Captures what’s important to be successful as a data scientist.” Eric Colson, Former Data Executive at Stitch Fix, Netflix

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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology

Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite.

About the book

How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself.

What’s inside

• How to coach and mentor team members
• Navigate an organization’s structural challenges
• Secure commitments from other teams and partners
• Stay current with the technology landscape
• Advance your career

About the reader

For data science practitioners at all levels.

About the author

Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies.

Table of Contents

1. What makes a successful data scientist?
2. PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP
3. Capabilities for leading projects
4. Virtues for leading projects
5. PART 2 THE MANAGER: NURTURING A TEAM
6. Capabilities for leading people
7. Virtues for leading people
8. PART 3 THE DIRECTOR: GOVERNING A FUNCTION
9. Capabilities for leading a function
10. Virtues for leading a function
11. PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY
12. Capabilities for leading a company
13. Virtues for leading a company
14. PART 5 THE LOOP AND THE FUTURE
15. Landscape, organization, opportunity, and practice
16. Leading in data science and a future outlook