Beyond Prediction: Why Your Business Needs Causal Inference

Title: Beyond Prediction: Why Your Business Needs Causal Inference

Abstract:
Every data professional knows how to build a model that predicts what will happen. We can predict which customers might churn, which patients are at high risk, or which users will click an ad. But predictive models have a massive blind spot: they cannot tell you what will happen if you actively intervene to change the outcome.
To answer critical business questions—like whether a new outreach strategy actually increased ROI, or if the change was just natural variation—we must move beyond standard machine learning and step into the world of causal inference.
In this talk, we’ll bridge the gap between predictive modeling and causal frameworks. We’ll explore real-world business scenarios where relying solely on predictive analytics leads to strategic mistakes, and demonstrate how causal approaches isolate true impact to drive better decision-making.

Speaker: Iman Alodah
Iman Alodah is a Senior Data Scientist with over seven years of experience applying advanced machine learning and statistical modeling to drive impactful healthcare solutions. Currently leading data initiatives as the Senior Data Scientist at Lucet Health, Iman holds a Master’s degree in Computer Science from Purdue University. Beyond her technical expertise, she is a dedicated community leader who has co-organized the Brilliant Women in Data Science meetup from 2022 to April 2026, fostering a thriving environment for collaboration, continuous learning, and professional growth.

As always free food and drinks. Come at 6PM to socialize and 6:30pm is the presentations.