SKILLS
- Programming Languages: Python (Pandas, Scikit-learn, PySpark, NumPy), SQL, R, Excel Functions
- Machine Learning: XGBoost, quantile regression, PyTorch, YOLOv8, RAG / FAISS, model evaluation
- Platform Tooling: AWS, Databricks, Docker, Jira
- Professional Certifications: Databricks Certified Data Engineer Associate, Databricks Certified Generative AI Engineer Associate, AWS Certified Cloud Practitioner
PROFESSIONAL EXPERIENCE
Northwell Health New York, NY
Senior Corporate Financial Analyst
June 2026 - Present
- Co-lead a decade-long legacy system modernization that transitioned Excel-based workflows to a full-stack web application and trained end users to ensure seamless adoption across CBO and Hospital posting teams
Corporate Financial Analyst
September 2024 - May 2026
- Secured executive buy-in from Vice Presidents and Senior Managers, gaining approval to migrate 140 users onto the new platform and delivering nine training sessions to drive full adoption across the department
- Architected Python and SQL medallion pipelines (bronze, silver, gold) reconciling $24B+ in annual transactions across five banking institutions, four AR systems, and Northwell's General Ledger
- Automated Batch Distribution Form generation process for Epic Health Systems AR postings, saving an estimated 1,200 hours and $230,000+ in labor costs across ~3,500 monthly forms
- Designed and deployed a PowerApps platform backed by a relational SharePoint database for data entry, replacing an error-prone shared Excel system, and eliminating ~90% of data entry errors
TECHNICAL PROJECTS
AI Faceless Video Generation Platform
- Architected and deployed a full-stack AI video generation platform, developing the complete codebase in collaboration with Claude Code (VS Code integration) as an AI coding assistant
- Built a cloud-native backend on Neon (serverless Postgres), Upstash Redis for async job queue management, Render for long-running worker deployment, and Cloudflare R2 for storage (no egress costs)
Surgical Procedure Duration Forecasting
- Designed, trained, and deployed machine learning system to predict Mohs (skin cancer removal) surgery duration for UVA Health clinical operations, achieving <10% prediction error on 90% of samples
- Applied XGBoost quantile regression on 10,000+ patient records in a Jupyter notebook using a remote GPU-powered server (Rivanna), demonstrating cloud-based compute practices for model training
Travel Advisor LLM
- Built a production-style retrieval-augmented generation (RAG) pipeline leveraging LLMs and FAISS-based vector search over structured documents, reducing hallucinated locations by 3x
- Built evaluation pipelines to measure hallucination rate, and reasoning performance using GSM8K, and synthetic benchmarks
Cloud Resume Challenge
- This site — built by hand on AWS (S3, CloudFront, Route 53, ACM, Lambda, API Gateway, DynamoDB) with IaC and CI/CD via GitHub Actions
EDUCATION
University of Virginia
M.S. Data Science, GPA: 3.9/4.0May 2026
B.A. Cognitive Science