Nihal Pai

MMM Joint Degree Candidate · MBA + MS Design Innovation

B.S. Computer Science · Magna Cum Laude

BMW Group Asia · Innovation Team — Data Science & Machine Learning internship

• Led implementation of core Python and Airflow features for a high-throughput genomics pipeline supporting reliable parallel processing and patient-sample data delivery across 5+ clinical and research programs.
• Partnered with clinical geneticists, laboratory teams, and engineers to identify workflow bottlenecks, define requirements, and evaluate architecture and delivery tradeoffs.
• Defined PostgreSQL data models and production quality signals spanning sample, laboratory, and pipeline activity to improve traceability and surface failures early.
• Automated cloud data-retention policies to reduce manual cleanup and address growing storage costs.

• Developed a data pipeline for the NIH-funded eMERGE study, automating result processing, quality checks, and clinical reporting across 155K+ genetic risk results.
• Helped operate and enhance a production system moving COVID-19 sample and result data from intake to reporting for hospitals, schools, and public-health partners.
• Built reusable onboarding, validation, and delivery capabilities across genomics programs.

• Translated nurse protocols and medication-program requirements into configurable product workflows for a digital patient-adherence platform serving 4+ pharmaceutical clients.
• Engineered full-stack capabilities supporting onboarding, communication, medication management, and treatment-stage-dependent behavior.

• Designed health-analytics dashboards and patient-onboarding interfaces during Techstars' UnitedHealthcare accelerator.
• Created a reusable visual system that helped engineers present clinical data clearly to care teams.