How to Lead in Data Science

Chong, Jike

ISBN 10: 1617298891 / ISBN 13: 9781617298899

Edité par Manning, 2021

A propos de cet article

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Détails bibliographiques

• Titre: How to Lead in Data Science
• Éditeur: Manning
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 1617298891
• ISBN à 13 chiffres: 9781617298899
• Reliure: Paperback
• État de l'article: New

A propos de ce titre

Synopsis

To lead a data science team, you need to expertly articulate technology roadmaps, support a data-driven culture, and plan a data strategy that drives a competitive business plan. In this practical guide, you'll learn leadership techniques the authors have developed building multiple high-performance data teams.

In How to Lead in Data Science you'll master techniques for leading data science at every seniority level, from heading up a single project to overseeing a whole company's data strategy. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Throughout, carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and show development areas to help advance your career.

Leading a data science team takes more than the typical set of business management skills. You need specific know-how to articulate technology roadmaps, support a data-driven culture, and plan a data strategy that drives a competitive business plan. Whether you're looking to manage your team better or work towards a seat at your company's top leadership table, this book will show you how.

À propos de l?auteur

Dr. JikeChong and Yue Cathy Chang have both built, led, and grown multiple high-performing data teams.

Dr. Chong developed the Yiren Digital Ltd. data team from the ground up, expanded and led the data team as chief data scientist at Acorns, and recently led the Hiring Marketplace Data Science team at LinkedIn.

Yue CathyChang and her team "parachuted" into companies to address challenging and meaningful data needs. She has worked with leaders of centralized and distributed data teams at organizations big and small, including large asset-management firms and Fortune 50 companies.