Summary
Jyoti Kumar is a biostatistics-trained data analyst and research assistant with 13 years of experience translating messy, multi-year biomedical datasets into actionable evidence at Columbia University. She has led quantitative analyses—cleaning, integrating, visualizing, and statistically modeling discontinuous datapoints in preclinical radiation studies—and is practiced at distinguishing true signals from outliers that could skew results. Proficient in R, SQL, and Python, Jyoti combines statistical modeling with domain knowledge in health economics and basic financial interpretation to assess stakeholder risk and ROI implications. Her background in mathematical physics (per her GitHub bio) and wet-lab research gives her a rare blend of theoretical rigor and practical experimental insight. She has also mentored students, organized academic symposia, and coordinated cross-school interprofessional initiatives, showing aptitude for coalition-building and science communication. Based in New York, she looks at long-term trends to de-risk projects and craft evidence-based strategies that anticipate downstream impacts.
13 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Biology/Biological Sciences, General, Bachelor of Science - BS, Biology/Biological Sciences, General at North Carolina State University
Master of Science - MS, Biostatistics, Master of Science - MS, Biostatistics at Columbia University Mailman School of Public Health