Health Analyst

Objective

Biostatistics graduate student at Columbia with experience in health data analytics, outcomes research, and market access insights. Skilled in R, SQL, and Python with a proven ability to support data-driven decision-making, synthesize research, and contribute to client deliverables in fast-paced, cross-functional teams.

Education

Columbia University New York, NY

MS, Biostatistics in Public Health Data Science. GPA 3.8 (Expected) May 2026 Relevant Coursework: Data Science, Statistical Inference, Advanced Statistical Computing, Biostatistical Methods

University of California – Berkeley Berkeley, CA

BS, Chemical Biology, Minor in Data Science. GPA 3.6 / Dean’s List 2023 May 2023

Relevant Coursework: Quantitative Methods in Biology, Multivariable Calculus, Programming in Python

Professional Experience

Genentech South San Francisco, CA

Scientist I June 2023 – June 2024

Contributed to cross-functional modeling projects by presenting predictive insights that shaped drug-target prioritization strategy.

Designed and implemented automation tools in R/Python that improved reporting turnaround by 40%, enhancing project timelines and deliverable quality.

Collaborated closely with analysts and scientists to ensure alignment between data interpretation and stakeholder needs.

Seoul National University - Lab of Immune Tolerance Seoul, South Korea

Research Intern June 2024 – August 2024

Conducted independent analysis of scRNA-seq datasets to identify immunological biomarkers and support downstream therapeutic exploration.

Streamlined analysis pipeline and enhanced reproducibility by 18%, supporting faster insight generation for internal teams.

Created structured documentation to improve team onboarding and knowledge transfer.

Samsung Bioepis, Inc. Incheon, South Korea

Research Intern July 2022 – August 2022

Conducted root-cause analysis and cost modeling on resin utilization across production batches.

Delivered findings through interactive dashboards and executive-ready visualizations using Excel and Tableau, directly supporting long-term strategic planning.

UC Berkeley – Miller Lab Berkeley, CA

Undergraduate Research Assistant August 2021 – December 2022

Developed a data extraction pipeline that improved analysis accuracy and reduced manual processing by 50%.

Synthesized lipid analysis findings and collaborated with lead researchers to redesign experiment flow for increased data reliability.

Projects

Philippines Nutrition Intervention – Project Lead UC Berkeley January 2023 – May 2023

Managed a 4-person project team to assess regional nutritional gaps using secondary research and stakeholder interviews.

Delivered a structured report with policy-focused recommendations tailored to community needs, mirroring consulting-style client deliverables.

Led presentation development and aligned insights with health system priorities and regional data.

Skills & Certification

Data & Analysis: SQL, R, Python, Tableau, Excel Certificate: Google Data Analytics Professional Certificate (Aug 2023)

Methods: Quantitative analysis, qualitative synthesis, regression modeling, data visualization, reproducibility optimization

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