This course is for students who want to learn how to manage data scientists and data science projects. This course connects real-world data on consumers and firms to decision-making and marketing management. The course will cover many real-world marketing examples to illustrate applications of methods used in data science. The use of real-world examples and cases places these techniques in context and teaches students how to avoid the common pitfalls of data science management, emphasizing the proper application of data science techniques and pipelines. In addition, the course focuses on the unique requirements for managing data science teams and projects. This course covers the considerations that go into starting and completing data successful data science projects in both small and large firms.

The goal of this course is three-fold. After taking this course you should:

• Approach business problems data-analytically. Think carefully & systematically about whether & how data can improve business performance.
• Be able to interact competently on the topic of data science. Know the basics of data science processes, algorithms, & systems well enough to interact with CTOs, expert data scientists, and business analysts. Be able to envision data-science opportunities.
• Be able to manage data science projects in marketing: Learn how to build a strong team by understanding the different roles needed to support both large and small scale projects. Learn how to mitigate risks in data science product delivery.

Shawndra Hill

Senior Lecturer

Dr. Shawndra Hill joined the Marketing Division at Columbia Business School as a part-time senior lecturer in September 2020. She received her PhD and MPhil in Information Systems from NYU's Stern School of Business in 2007 and 2003 respectively, and her BS in Mathematics from Spelman College and her BEE in Electrical Engineering from Georgia Institute of Technology  in 1995.  Presently, Shawndra Hill is also...

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