Data/ML Engineer building production data pipelines in healthcare and biotech. Currently a Research Technician II at Cleveland Clinic's Center for Immunotherapy and Precision Immuno-Oncology, where my work spans ML pipeline development, spatial proteomics analysis, and clinical database management — well beyond the title.

🎯 Looking for: Data Engineer / ML Engineer roles (remote, or hybrid in Akron/Cleveland, OH) 🎓 Currently: Finishing an M.S. in Data Science at the University of Pittsburgh (expected 2027) 🔧 Building: A dbt + Postgres data warehouse for job market analytics (star schema, CDC, Type-2 SCD)

akoya-pcf-pipeline Production pipeline processing spatial proteomics imaging data (Akoya PhenoCycler Fusion) end-to-end — ingestion, illumination correction, cell segmentation (Cellpose), feature extraction, phenotyping (Scanpy/Leiden/UMAP), and spatial analysis (Squidpy). Containerized with Docker, GitHub Actions CI/CD, and HPC/Slurm deployment. Python Docker Cellpose Scanpy Squidpy HPC

lab-accession-app Desktop application that replaced a 47-sheet shared Excel accession log with a real SQLite-backed system. Packaged and cross-platform (Windows/Mac) via PyInstaller and GitHub Actions CI/CD; demoed to lab staff with positive feedback. Python CustomTkinter SQLite PyInstaller

job_market_analyzer Data pipeline analyzing job market trends — currently being rebuilt into a proper star-schema warehouse (fact/dimension tables, dbt snapshots for Type-2 SCD, CDC) on Supabase Postgres. Python dbt PostgreSQL ETL

Languages: Python, SQL Data Engineering: dbt, Snowflake, ETL/ELT pipeline design, SQLite, PostgreSQL ML / Analysis: scikit-learn, statsmodels, Scanpy, Squidpy, Cellpose Infrastructure: Docker, GitHub Actions (CI/CD), HPC/Slurm Domain: Healthcare data, HIPAA-compliant systems, clinical databases

LinkedIn · Cleveland, OH