Key questions to ask when managing data science projects


Data science managers (and senior leaders managing data science teams) need to think through many questions relating to how to best execute their data science efforts. For example, what is the most effective way to lead a data science project? How to make sure my data science team does not expose my organization to issues relating to the misuse of data and/or algorithms? How do I validate the results provided by the data science team?

This workshop will explore these questions and many others. The focus of this not on which specific algorithms a team should use, but rather, how to ensure an effective and efficient data science team. Areas to be explored include:

Managing Data Science Teams, such as:
o Structuring and coordinating data science functions/capabilities
o Coordinating IT, analytic and client teams
o Staffing/training data science teams
o Ensuring ethical data usage and model development/deployment
o Enabling data and model transparency

Improving processes to develop and deploy analytical models, such as:
o Tools and platforms to support modular data science practices
o Agile data science process methodologies
o Analytic model workflow management
o Analytic model life-cycle management

Exploring Chief Data Officer & Chief Analytics Officer responsibilities, such as:
o Exploring innovative data science governance approaches
o Business value of analytics and analytical governance
o Managing project and deployment risk
o Ensuring data and model ownership
o Designing, staffing and directing data & analytics governance

Ensuring data and model asset management, including:
o Model management platforms
o Model documentation and transparency
o Model compliance management
o Analytics regulatory risks and risk mitigation


Jeff Saltz is an Associate Professor at Syracuse University, where his research and consulting focus on helping organizations leverage data science and big data for competitive advantage. Specifically, his work identifies the key challenges, and potential solutions, relating to how to manage, coordinate and run data science / big data projects within and across teams. In order to stay connected to the real world, Jeff consults with clients ranging from professional football teams to Fortune 500 organizations. In his last full-time corporate role, at JPMorgan Chase, he reported to the firm’s Chief Information Officer and drove technology innovation across the organization. Saltz received his B.S. in computer science from Cornell University, an M.B.A. from The Wharton School at the University of Pennsylvania and a Ph.D. in Information Systems from the NJIT.

Open Data Science




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