I am a hands-on full-stack data science leader at Mission Lane where I lead our Automation group (Machine Learning Engineering) and do side work in model fairness. We're building a unified feature store and a model auto-rebuilding platform to enable our partners to see the potential impact of new models and deploy them quicker. Prior to this role, I led model development to deliver millions in PV for our Card business.Prior to Mission Lane, I spent 7 years at Capital One working in the Auto Finance vertical building models to optimize valuations, pricing, marketing, and operations. I also spent three years in model risk management leading model validations across the business and becoming a Model Risk Officer.I graduated with a PhD in Statistical Science from Duke University in 2014. My dissertation research under Alan Gelfand involved developing methods for model validation and inference for Bayesian spatial point process models.Proficiencies: Python, SQL, Airflow, XGBoost, LightGBM, Git, Unix, Spark, R, Cloud Computing.Familiar with: Kubernetes, Docker.
Listed skills include R, Data Analysis, Bayesian Statistics, Sas, and 7 others.