How to Lead in Data Science

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, NetflixIn How To Lead in Data Science you will learn:Best practices for leading projects while balancing complex trade-offsSpecifying, prioritizing, and planning projects from vague requirementsNavigating structural challenges in your organizationWorking through project failures with positivity and tenacityGrowing your team with coaching, mentoring, and advisingCrafting technology roadmaps and championing successful projectsDriving diversity, inclusion, and belonging within teamsArchitecting a long-term business strategy and data roadmap as an executiveDelivering a data-driven culture and structuring productive data science organizationsHow 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 technologyLead 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 bookHow 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 insideHow to coach and mentor team membersNavigate an organization’s structural challengesSecure commitments from other teams and partnersStay current with the technology landscapeAdvance your careerAbout the readerFor data science practitioners at all levels.About the authorDr. 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 Contents1 What makes a successful data scientist?PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP2 Capabilities for leading projects3 Virtues for leading projectsPART 2 THE MANAGER: NURTURING A TEAM4 Capabilities for leading people5 Virtues for leading peoplePART 3 THE DIRECTOR: GOVERNING A FUNCTION6 Capabilities for leading a function7 Virtues for leading a functionPART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY8 Capabilities for leading a company9 Virtues for leading a companyPART 5 THE LOOP AND THE FUTURE10 Landscape, organization, opportunity, and practice11 Leading in data science and a future outlook

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