| Description |
1 online resource (1 volume) : illustrations |
| Bibliography |
Includes bibliographical references. |
| Summary |
As a discipline, data science is relatively young, but the job of managing data scientists is younger still. Many people undertake this management position without the tools, mentorship, or role models they need to do it well. This report examines the steps necessary to build, manage, sustain, and retain a growing data science team. You'll learn how data science management is similar to but distinct from other management types. Michelangelo D'Agostino, VP of Data Science and Engineering at ShopRunner, and Katie Malone, Director of Data Science at Civis Analytics, provide concrete tips for balancing and structuring a data science team. The authors provide tips for balancing and structuring a data science team, recruiting and interviewing the best candidates, and keeping them productive and happy once they're in place. In this report, you'll: Explore data scientist archetypes, such as operations and research, that fit your organization Devise a plan to recruit, interview, and hire members for your data science team Retain your hires by providing challenging work and learning opportunities Explore Agile and OKR methodology to determine how your team will work together Provide your team with a career ladder through guidance and mentorship. |
| Subject |
Information technology -- Management.
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Teams in the workplace.
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Personnel management.
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Computer engineers -- Selection and appointment.
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Personnel Management |
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Technologie de l'information -- Gestion. |
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Équipes de travail. |
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Personnel -- Direction. |
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Informaticiens -- Sélection et nomination. |
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Information technology -- Management |
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Personnel management |
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Teams in the workplace |
| Added Author |
Malone, Katie, author.
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