Moazam Ali

Defined and standardized end-to-end SaaS KPIs across the user lifecycle as tested dbt models unifying Stripe, PayPal, and RevenueCat subscription data. Conducted retention and cancellation analyses, built a probabilistic cohort-level LTV/CAC model, and designed an A/B testing framework for pricing and onboarding-flow experiments.

Built self-service dashboards consolidating multi-source advertising data (Meta, Google) in Retool to track lead conversion rates and top-of-funnel performance. Implemented low-code automation workflows using Retool and Zapier to streamline reporting and internal operations.

Deconstructed the delivery operation into key cost drivers, enabling detailed cost analysis that helped leadership reduce cost-to-serve. Designed and executed area-based pricing A/B tests, built geo-spatial dashboards using the h3 library, and modeled customer lifetime value using Gamma and Beta-Geometric distributions.

Taught the application of inferential statistics and econometric modeling in business and social science research to undergraduate students. Redesigned lab modules to enhance understanding of Linear Algebra and Probability in econometric models using visualizations and simulations in Stata and Python.

Pursuing credit courses in Applied Mathematics, covering deep learning, applied probability, discrete mathematics, calculus, and linear algebra.

Grade: 3.48/4.00

Completed a Bachelor of Sciences in Finance with a CGPA of 3.48/4.00, covering econometrics, business analytics, statistical inference, and financial risk management.