Partner with product and engineering to develop product roadmap and translate roadmap into concrete team projects.Coordinate a team of 5 - 10 engineers and data scientists to implement new product features.Develop machine learning algorithms to improve quality of provider recommendations being served to health insurance members.

Use machine learning to profile providers and serve optimized primary care physician recommendations to client members.Evaluating expected and actual outcomes of primary care assignments delivered by Nuna to iterate and improve on recommendation algorithm.Migrating machine learning pipeline to a more scalable, testable system to support future client deployments and more effective algorithm iteration.

Designing and building scalable data pipelines to support delivery of value based healthcare programs.Partnering with critical anchor clients to launch applications to hundreds of client partners.

Measuring population risk profiles with machine learning to facilitate the delivery of value based healthcare.Quantifying quality of care given by individual providers to improve health outcomes for patients.

Addressing open ended business questions in a team oriented environment by delivering quantitative analytics and qualitative analysis. My work has spanned across a variety of practice areas including consumer protection, mortgage backed securities, intellectual property, and independent market studies helping me to develop a dynamic problem solving approach.Trademark Clearing House (TMCH) Services Review • Designed and conducted analyses to assess the value of TMCH to stakeholder groups • Developed data driven insights from numerous data sources about value of TMCH features • Collaboratively supported academic experts in written report published by ICANN for review by international internet administration communityConsumer Protection - Evaluation of Multilevel Marketing Organization • Analyzed recruitment behavior, churn rates, and member payment and purchase history • Synthesized information from numerous datasets including sales records, recruitment, and shipments • Formulated and evaluated concise research questions with client, academic expert, and internal team

Capstone Project - RedistrictR • Developed more equitable voting districts based on rigorous, quantitative methodology • Deployed evolutionary algorithm in python to traverse vast set of potential district assignments • Parallelized algorithm across cluster of AWS EC2 instances • Gathered and reconciled data from multiple sources using spatial techniquesiMentor Consulting Project • End to end data science project encompassing collection, storage, analysis, and deliverable • Analyzed message traffic between mentors and mentees to identify indicators of mentor dropout • Identified decreasing mentor engagement over time leading to eventual dropout • Presented findings to iMentor to improve engagement and retention of future program volunteers