We’re seeking a Data Scientist I to support experimental research programs through the analysis and visualization of biological datasets. This role sits at the intersection of data science and experimental biology — ideal for someone who enjoys collaborating with scientists, exploring complex datasets, and helping translate data into actionable experimental insights.
You’ll work closely with experimental and computational teams to clean, join, and interpret data from multi-assay experiments, helping guide next-step decisions in discovery research.
- Ingest, clean, and join large experimental datasets (e.g., biochemical assays, plate maps, metadata) using Python (pandas, numpy).
- Implement reproducible analyses via notebooks and scripts.
- Apply appropriate statistical summaries and visualizations tailored to biological context.
- Perform QA/QC checks (sanity checks, outlier detection) to ensure data integrity.
- Generate clear visualizations and concise exploratory data analysis (EDA) summaries to support decision-making.
- Collaborate with experimental scientists to understand assay design, objectives, and success criteria.
- Translate technical findings for non-technical audiences.
- Contribute to building high-quality datasets that may support future modeling or AI applications.
- Master’s degree in a relevant technical discipline (e.g., bioinformatics, computational biology, data science, biostatistics) with limited industry experience or
Bachelor’s degree with 2+ years of relevant industry or research experience.
- 1–3 years of experience analyzing experimental or biological datasets (academic, startup, or industry).
- Strong proficiency in Python and the data science stack (pandas, numpy, data visualization, Jupyter workflows).
- Solid grasp of exploratory data analysis and basic statistics (distributions, confidence intervals, hypothesis testing).
- Ability to understand experimental context and partner effectively with bench scientists.
- Excellent communication skills — able to explain technical results clearly and concisely.
