work
since 2016
Experience
- 2022 – now
Lead Data Scientist / Tech Lead
Medicaid Consumer Analytics & Behavior Change Team
Lead a small DS team on Medicaid behavior change — $20M+ in active programs, internal tooling (launch-box, caliper), and the team's agentic-coding practice.
- Own the condition and medication management intervention portfolio across Medicaid — programs the team runs today generate $20M+ in annual medical cost savings.
- Identified Rx Fraud, Waste & Abuse as an untapped intervention area, sizing it at $93M–$310M annually (AMCP 3–10% benchmarks on $3.1B spend) and narrowing to a $12.4M actionable pattern. First validating campaign launched; response analysis underway.
- Building the Diabetes Care Navigator, a member-journey framework orchestrating diabetes-related next-best-actions: simulation-based sizing on a diabetes progression model, and a repeatable path from call-to-action to targeting rules to medical/Rx value. Spun out an agent-driven Python → notebook → HTML → deck workflow.
- Built launch-box, an internal bootstrapper for DS shipping GKE-deployed analytical apps — a questionnaire generates a deployment-ready repo with infra, templates, branding, and docs, cutting time-to-market from weeks to hours. Added skills that scaffold features on request (e.g. secret management).
- Built the Health Plan grid manager, a launch-box-bootstrapped Streamlit app giving marketing partners one place to manage plan details shown on creatives — replacing a hand-passed spreadsheet with a single source that feeds downstream pipelines automatically and stays consistent.
- Architected caliper, an evaluation framework for next-best-action campaigns — codifies impact measurement, automates monthly financial refreshes, hosts dashboards. Replaces per-campaign one-offs: more rigor, less duplication, more DS time for modeling.
- Drive the team’s agentic-coding practice through mentoring and knowledge sharing, alongside standards for code review, linting, and environments. Part of the org-wide Claude Trailblazers cohort, a small group meeting regularly to push AI adoption and best practice across the org, and one of three on the pre-event training & readiness workstream for an internal AI hackathon.
- 2020 – 2022
Senior Data Scientist
Medicaid Consumer Analytics & Behavior Change Team
Shipped the team's first Rx adherence NBA and the foundational team infrastructure (Medipedia + shared Python library) still in use today.
- Designed and launched the first Rx adherence next-best-action for Medicaid — an XGBoost model flagging high-risk members for daily outreach. A randomized controlled trial measured a +2% lift in medication adherence (PDC), worth $7M+ in annual medical cost savings at launch. The program has grown since — roughly $11M a year today.
- Shipped further NBAs across the chronic-condition portfolio — diabetes A1c testing, inhaler education, respiratory follow-up — each evaluated on condition-specific care and financial metrics. A1c testing joined Rx adherence among the largest cost-saving programs still running today.
- Built Medipedia, a GitHub Pages knowledge base for onboarding, Medicaid data conventions, and project docs, alongside a shared Python library for common DS tasks. Both remain in active use, and treating internal infrastructure as a deliverable led a teammate to build libraries of their own.
- 2017 – 2020
Data Scientist
Tech team
First data hire at a short-term rental startup — built and owned the company's data, BI, and supporting backend stack.
- Joined as the first data hire and built the foundational infrastructure before DS work could land — 20+ ETL pipelines (BigQuery + Airflow + Pub/Sub on GCP) ingesting TBs, plus curated BI views and Chartio dashboards for 100+ stakeholders. Chose Chartio over Tableau and Looker on stage and budget.
- Stretched into backend engineering to keep the stack running — APIs, DB migrations, deployment pipelines, and a JupyterHub deployment that standardized notebook-based runbooks across the org.
- Built recursive web-scraping pipelines compiling a database of 1M+ U.S. short-term rental listings, feeding market-entry decisions (which cities to expand into) and pricing benchmarks against comparable properties.
- Co-led hiring as the team grew — brought in a tech Lead (the team’s first manager), an additional DS, multiple engineers, and an SRE. Coached 30+ non-technical stakeholders on reading and acting on data, building a data-driven culture across the company.
- 2017
Associate
Integrated Consumer Banking Solutions Team
Bank-benchmarking analytics on Argus' multi-bank consortium data; introduced Python to a SQL/Excel-only team.
- Built benchmarking analyses for commercial banking clients against Argus’ multi-bank consortium dataset — identified opportunities to grow deposit portfolios by millions.
- Modeled and presented strategy recommendations to client executives — including a projected 18% lift in customer retention from P2P payments adoption, drawn from behavioral patterns across the consortium.
- Introduced Python to a SQL + Excel–only team, streamlining batch workflows and onboarding 5+ colleagues to scripted analysis.
- 2016
Fall Intern
Wholesale Credit Analytics and Solutions (WCAS)
Fall intern with Wholesale Credit Analytics — SQL and Bash scripting on terabyte-scale credit data.
- Scripted Bash automations to replace manual report uploads to remote systems.
- Ran SQL queries over TB-scale credit data for risk-assessment reports; partnered with the quant research team to reconcile outputs and tighten technical documentation.
Education
- 2015 – 2016
Master in Mathematics of Finance
Columbia University
- Example coursework: Time-Series Modelling, C++ Programming for Quantitative and Computational Finance, Numerical Methods in Finance, Multi-Asset Portfolio Management, Financial Risk Management.
- Course project: Web-based Risk Calculation Engine.
- 2016
Fellowship in Data Science
The Data Incubator
- Intensive data science bootcamp admitting fewer than 3% of thousands of applicants.
- Weekly projects: identifying popular celebrities using web scraping and network analysis; analyzing restaurant inspection data with SQL; predicting Yelp score using scikit-learn; Wikipedia linguistic analysis via MapReduce.
- Capstone project: analyzed NYC taxi and Uber trip data; built a web application to predict cab fare and trip duration given locations.
- 2011 – 2015
Bachelor in Double major: Mathematics-Economics & Dance
Wesleyan University
- Honors thesis in Mathematics-Economics.
- Dean’s List.
- Completed the Dance major after starting to dance freshman year.