Leading team of data scientists to build Dynamic Targeting, which uses real-time data to orchestrate salesforce interactions, ensuring the right sales reps engage with the right customers at the right time.

- Created and delivered quarterly Marketing Mix Models (MMM) measuring ROIs for 17 brands and $500M+ in annual spend. - Led development of an automated modeling pipeline and dashboard to democratize MMM insights directly to leadership (2022 CIDO award winner).- Wrote a programming framework used by the data science team at Lilly to create modular and reproducible projects at scale.- Designed, executed, and analyzed marketing experiments costing $80M across DTC, digital, and doctor-level marketing. Insights led to $40M+ in savings and added revenue.- Built predictive models to dynamically identify high-value doctors, improving sales targeting by 20%+ over existing approaches (2021 Colonel Award Winner).- Team lead of 4 data scientists in US and India driving LillyUSA’s advanced analytics capabilities. Fostered a team culture emphasizing business impact, open communication, and technical excellence.- Assisted in the interview process of 30+ US and abroad candidates.- Partnered with marketing leadership to translate business problems into analytics projects that impacted $1B in annual spend. - Methodology: machine learning, regression, predictive models, causal inference, matching, designed experiments, optimization, mixed and generalized linear models, clustering.

Lectured MS and PhD students on Financial Econometrics, Python, and Matlab. Managed teaching assistants, and developed new lecture materials. All materials are available on my website.

Tutored MS and undergraduate students on Financial Econometrics, Options and Futures, and Introduction to Econometrics. Assisted professors on developing lecture notesand exams.

Tutored MS students on Mathematics for Economists. Assisted professor on grading.