Leading Data Science Teams

Compared to other functions of an organization, data science is highly speculative. Data science teams are often tasked with last-minute must-have deliverables that are well beyond their ability to produce. Data might be missing or have no signal, or the data models themselves might be impractical. This hands-on reference guides team leaders through the types of challenges you might face and the tools you need to work through them.

Author Jacqueline Nolis, head of data science at Saturn Cloud, helps team leaders think through the various issues you'll encounter when running a data science team. You'll learn ways to set up your team, manage data scientists to promote their success, and collaborate with external stakeholders. Once you finish this report, you'll be ready to work through the challenges your current team faces or start a new data science team in an organization that needs one.

• Determine the scope of work before choosing your team of data scientists and support positions
• Successfully manage your relationship with stakeholders by providing your team with clear, achievable goals
• Create an environment to help data scientists and other team members succeed
• Choose a technical infrastructure for your team, including programming languages, databases, and deployment models