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.

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?

PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP

2 Capabilities for leading projects

3 Virtues for leading projects

PART 2 THE MANAGER: NURTURING A TEAM

4 Capabilities for leading people

5 Virtues for leading people

PART 3 THE DIRECTOR: GOVERNING A FUNCTION

6 Capabilities for leading a function

7 Virtues for leading a function

PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY

8 Capabilities for leading a company

9 Virtues for leading a company

PART 5 THE LOOP AND THE FUTURE

10 Landscape, organization, opportunity, and practice

11 Leading in data science and a future outlook

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