Data Scientist

Join the Corradin Lab at Whitehead Institute in Cambridge, MA (onsite) , where data science supports investigations into human genetic and epigenetic variation tied to neurological disease. In this role, you will apply machine learning and computational biology to develop tools and analyze complex biological datasets, helping translate functional genomics experiments into actionable insights. What you'll do The Data Scientist will design and build computational approaches for biological data analysis, with a focus on experiments such as single cell RNA-seq , multiomics , and CRISPR perturbation . Use programming skills to create computational tools for biological data analyses, including single cell RNA-seq, multiomics, and CRISPR perturbation experiments Analyze experimental data and address methodological challenges, including data integration Prioritize and organize workflow with discretion while optimizing methodologies and results Develop and apply algorithms for analysis of large-scale biological data across multiple projects Perform hypothesis testing using statistical concepts Apply machine learning methods such as classification, regression, and clustering to support diverse research questions Optimize efficiency for NGS data analysis Collaborate closely with internal and external collaborators Leverage LLMs and machine learning for genomics Support additional duties, as assigned What you bring PhD degree in biology or a data science-related field 2+ years of experience in computer programming Proficiency in Python , Unix/Linux OS , and/or R Experience processing NGS data (preferred) Knowledge of statistical tests and machine learning algorithms Data visualization experience in Python or R Tools and focus areas You will work with Python , Unix/Linux OS , R , and genomics workflows including single cell RNA-seq, multiomics, CRISPR perturbation experiments, and NGS data analysis, with added opportunities to apply LLMs and machine learning for genomics. Compensation USD 85,000 to 100,000 per year . #J-18808-Ljbffr