Sep 23–26, 2019
Subhasish Misra

Subhasish Misra
Staff Data Scientist, Walmart Labs

Subhasish is a staff data scientist at Walmart Labs, where he leads efforts to create scalable machine learning solutions for Walmart’s customer base. He’s also a member of the global data science board at I-COM, a cross-industry global think tank on harnessing data and analytics for better marketing. Previously, Subhasish was at HP, WPP, and Aon and consulted for many Fortune 500 clients across multiple geographies in his 12 years of advanced analytics career. His broad expertise lies along a wide spectrum of marketing analytics, and his current data science interest areas are around modeling customer behavior and causal inference. He holds an MA in economics from the Delhi School of Economics, where econometrics was one of his focus areas.


5:25pm6:05pm Wednesday, September 25, 2019
Location: 1A 12/14
Secondary topics:  Retail and e-commerce
Subhasish Misra (Walmart Labs)
Causal questions are ubiquitous, and randomized tests are considered the gold standard. However, such tests are not always feasible, and then you just have observational data to get to causal insights. But techniques such as matching offer an opportunity to solve this. Subhasish Misra explores this and practical tips when trying to infer causal effects. Read more.
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