Top Data Scientists

Hi, I'm Wayne. I enjoy solving business problems and driving results with data. At IHG, we provide optimal pricing for 6,000+ hotels globally. At UPS, we drove the Pricing models behind the B2B sales contracting tool for all US sales, Canada, and Europe. While at Georgia Tech, I was the CFO of Oculus Prime, a Georgia Tech-Emory biotech startup focused on a novel glaucoma treatment which won second place in the 2018 TYE Atlanta, and made it to the second round of the 2018 Rice Business Case Competition.

I love all things data, experimentation, and helping people make informed decisions.

I have a passion for combining cross-functional skills in engineering, modeling and business analysis to realize value in data-driven initiatives. I’m deeply driven by curiosity to learn from data and generate actionable insights. Known for my collaborative approach, high-quality code and effective visualizations.

Experienced Data Scientist with a demonstrated history of working in the e-commerce food delivery platform and management consulting industry. Skilled in Python (Programming Language), Machine Learning, Deep Learning, Natural Language Processing (NLP). Strong engineering professional with a Bachelor's degree focused in Information Technology from Jaypee Institute of Information Technology, Noida.

I'm a Senior Applied Data Scientist with 9+ years of experience building production ML systems for high-stakes decision environments across claims, healthcare, pharmacy, fraud, and financial risk.My strongest work sits where modeling, messy data, business judgment, and production ownership meet. I've led CatBoost and XGBoost models from ambiguous problem framing through feature development, training, validation, monitoring, retraining, stakeholder readouts, and production deployment support. That work has included reserve and indemnity models across a multi-billion-dollar claims portfolio, pharmacy Fraud/Waste/Abuse prioritization across 60k+ pharmacies, and population health modeling using large-scale medical and pharmacy claims data.At State Farm, I lead production reserve modeling work using millions of historical claim records, daily/monthly scoring workflows, and annual retraining and evaluation processes. One model improved test-set MAE by $1k+ per claim while supporting financially material reserve decisions. At OptumRx, I helped build the organization's first ML-driven pharmacy Fraud/Waste/Abuse model, using PySpark, XGBoost, and behavioral features over billions of prescription claims to improve audit prioritization.I'm especially interested in senior IC applied ML roles where production modeling, model monitoring, product impact, experimentation, and clear technical communication all matter. I like working close to real decisions: defining the problem, building reliable models, understanding when to trust them, and helping teams turn model outputs into better actions.

Data scientist using analytics and predictive models to streamline business process and increase business users efficiency.

5 years of experience as a data scientist specializing in fraud and risk, rec and personalization.