Interested in creating clean, production-ready Python projects across analytics, ML, and backend. I like analytical testing and simple dashboards that answer real questions.
- Analytics & ML in Python (pandas, scikit-learn)
- SQL modeling and KPI design (Postgres)
- Lightweight apps & APIs (Streamlit, FastAPI)
- CI, tests, and type hints for maintainability
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NFL QB Performance Analyzer — Streamlit app that engineers QB features and ranks performance via Ridge regression.
Python · pandas · scikit-learn · Streamlit · PyTest · CI
➜ https://github.com/mattwhittemore/nfl-qb-performance-analyzer -
Retail Sales Analytics — SQL + BI — Postgres schema + KPI queries (AOV, conversion, cohort) with a small export tool and tests.
SQL · Postgres · Analytics Engineering · PyTest · CI
➜ https://github.com/mattwhittemore/retail-sales-analytics-sql-bi -
Cloud OCR + NLP Pipeline (AWS) — Textract-style OCR → Pydantic validation → FastAPI service. Local runner + Lambda/Infra skeleton.
AWS · Textract (pattern) · FastAPI · Pydantic · Serverless · CI
➜ https://github.com/mattwhittemore/aws-ocr-nlp-pipeline -
Logistics Digital Twin — SimPy — Discrete-event simulation of a fulfillment center to explore throughput and SLAs.
SimPy · Operations Research · Python · PyTest · CI
➜ https://github.com/mattwhittemore/logistics-digital-twin-simpy