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Leading Data Science Teams

Unlock the Transformative Power of Data

Leveraging an organization’s data to implement strategic changes is an integral component in accelerating growth. In this seminar, you will gain training to drive growth and profitability by effectively using modern methods in statistics, econometrics, and machine learning to make optimal decisions informed by real-world data. This course is ideal for helping leaders use data science to attain actionable insights and create business value.

Upcoming course date

Thursday, September 22, 2022, 12:30-3:00pm PT

Benefits of attending this online course

  • Learn how to build a data-driven strategy.
  • Gain a better understanding of how data can be leveraged to address business solutions.
  • Utilize data-driven models for better decision-making.
  • Develop metrics to evaluate machine learning capabilities.
  • Understand how to better manage a team of data scientists.

Who should attend:

  • Data scientists who are responsible for managing a team of data scientists or department focused on data analytics.
  • Professionals with some technical background who want to learn how to apply analytics to make better business decisions.
  • Business managers and leaders who collaborate with data scientists and technical professionals responsible for driving growth strategies.

Leading Data Science Teams content overview

This course is taught by Hema Yoganarasimhan, Professor of Marketing and Director of the Foster Customer Analytics Center (FCAC) at the University of Washington Foster School of Business. The Foster Customer Analytics Center focuses on developing relationships among businesses, researchers, and students to create impactful real-world business applications, research, and education in the fields of machine learning and marketing analytics.

The course will provide a four-step process for how a modern data-driven manager can develop and leverage data-driven solutions.

Step one: You will learn how to take a big picture business problem and translate into a clean statistical model.

Step two: You will learn how to identify data sources (observational or A/B tests) that are needed to solve the problem. In this context, the class will look at the advantages and challenges associated with large-scale field experiments, strategies for working in data-sparse situations, and how to make the best of imperfect data.

Step three: Learn how to match the model with the right solution concept. We will cover a wide range of methods — descriptive models, predictive machine learning models, causal inference, and policy design based on field experiments.

Step four: We will discuss how to take the results from empirical models and design business policies, and how to evaluate the long-run profitability of these policies. We will conclude with a discussion of best practices for addressing emerging challenges and opportunities in data science, such as balancing privacy and profitability, algorithmic fairness, and consumer choice and welfare.

Registration and Fees

Dates and fees Registration
Wednesday, September 22, 2022, 12:30-3:00pm
$295
Register now
Deadline: September 15

Program fee includes instruction and learning materials. Payment must be made by credit card or UW budget transfer. It is strongly encouraged that you register early as space is limited. See discount and cancellation policies.

Hema Yoganarasimhan is a Professor of Marketing and Michael G. Foster Faculty Fellow with affiliate appointments in the UW’s Allen School of Computer Sciences and Engineering, Department of Economics, and Center for Statistics in the Social Sciences. She is the founding faculty director of the Foster Customer Analytics Center.

Recognized as one of the leading experts in quantitative marketing, Yoganarasimhan’s research brings together large-scale marketing data, economic theory, and econometric and machine learning tools to help firms optimize and automate marketing decisions. Hema’s research has won many prestigious awards, including the MSI Alden G. Clayton Doctoral Dissertation Proposal Award, Frank M. Bass Outstanding Dissertation Award, and John D.C. Little Best Paper Award. She has also been recognized as an “MSI Young Scholar” in 2015, an “MSI Scholar” in 2020, and an Erin Anderson Emerging Female Marketing Scholar and Mentor in 2021. She serves as co-editor of the journal Quantitative Marketing and Economics and as associate editor of Management Science and Marketing Science.

Hema received her Ph.D., M.A., and M.Phil. in Marketing and Business from Yale School of Management. Prior to that, she received her bachelor’s degree from the Indian Institute of Technology (IIT) Madras. She has been at University of Washington since 2014, where she teaches MBA and undergraduate classes on analytics for the “4Ps” of marketing and an advanced Ph.D. class on dynamic structural models.

Like our in-person courses, online courses from Executive Education are designed and led by Foster School faculty and taught using the same evidence-based research and application. Students will participate in discussions, breakout sessions, and direct interactions with our faculty. Courses are conducted via Zoom, which facilitates real-time interface between students and faculty via webcam and text-based chat.

Two weeks prior to the live class session, you will receive information about any pre-readings, assignments, or case studies that need to be completed before class.

In addition to the faculty, each course has an assigned Program Manager who will provide guidance throughout the course.