At Lifesight, I develop causal inference methods that improve marketing attribution, reduce upper-funnel bias in marketing mix models, and support more reliable investment decisions.
I've led geo-experiment analyses, built robustness-testing frameworks for MMM deployment, and applied Bayesian modelling, synthetic control, and quasi-experimental methods to estimate causal lift when randomized trials were infeasible.
Previously, I delivered machine learning and AI research across diabetes glucose monitoring, audio translation, image classification, object detection, customer churn prediction, and customer segmentation. I bring a business analytics and statistics foundation to responsible AI, experimentation, and decision-making.
