How to Lead in Data Science
eBook Details:
- Paperback: 512 pages
- Publisher: WOW! eBook (December 21, 2021)
- Language: English
- ISBN-10: 1617298891
- ISBN-13: 978-1617298899
eBook Description:
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
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.
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.
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 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.
