Causal Inference for Real-World Decision Making
Hosted by Anirban Bhattacharyya
Mon, May 4, 2026
5:00 PM UTC (30 minutes)
Virtual (Zoom)
Free to join
Mon, May 4, 2026
5:00 PM UTC (30 minutes)
Virtual (Zoom)
Free to join
What you'll learn
Choose the Right Causal Method for the Problem
Validate Assumptions and Diagnose Failure Modes
Communicate Causal Results for Better Decisions
Why this topic matters
You'll learn from
Anirban Bhattacharyya
Seasoned data scientist with more than 10 years of experience in data science
Anirban is a Senior Data Scientist at Atlassian with more than 10 years of experience applying analytics, experimentation, and causal inference to real-world business problems. Over the course of his career, he has worked at companies including Google, Dropbox, Pinterest, eBay, and American Express, where he partnered with product, growth, and marketing teams to drive better decisions through data.
His work has focused on high-impact questions such as measuring the effect of product changes, understanding customer behavior, optimizing growth initiatives, and evaluating interventions when clean randomized experiments are not possible. Across these roles, he has developed deep expertise in causal inference, statistical modeling, experimentation, and product analytics, with a strong emphasis on making rigorous methods useful in messy, high-stakes business settings.
Anirban brings a practical, industry-centered perspective to teaching. Rather than focusing only on theory, he is passionate about helping students learn how to choose the right causal method, validate assumptions, diagnose failure modes, and communicate findings in a way that earns stakeholder trust and drives action.
