Lead Analyst Jobs in Cambridge, MA

Job Summary: A leading biopharmaceutical organization is seeking a Bioinformatics Analyst III to support cutting-edge single-cell atlas initiatives focused on immunology research and target discovery. This role will analyze large-scale transcriptomic and epigenomic datasets, develop computational workflows, and collaborate with multidisciplinary teams to generate biological insights that advance therapeutic research. The ideal candidate will possess strong expertise in single-cell bioinformatics, Python programming, and computational biology.

Key Responsibilities:

• Curate, harmonize, and analyze large-scale single-cell transcriptomic and epigenomic datasets from internal and public sources.
• Integrate multi-modal datasets to support the development of comprehensive single-cell reference atlases.
• Develop and apply computational, statistical, and artificial intelligence or machine learning methods to identify cell states, regulatory networks, and disease-associated biological mechanisms.
• Analyze tissue-specific biology, fibroblast heterogeneity, and cellular interactions to support target identification and validation efforts.
• Collaborate with immunology researchers, computational scientists, and cross-functional teams to translate scientific questions into computational analyses.
• Design, implement, and optimize reproducible bioinformatics workflows for large-scale omics data analysis.
• Document data processing pipelines, analysis methods, and computational workflows to ensure reproducibility and transparency.
• Support time-sensitive research projects that contribute to therapeutic target discovery and prioritization.
• Present scientific findings and analytical results clearly to technical and non-technical stakeholders.

Required Qualifications:

• Master's degree with at least 5 years of experience, or Doctorate degree in Bioinformatics, Computational Biology, Computational Genetics, Computer Science, Biostatistics, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
• Strong experience analyzing single-cell RNA sequencing and single-cell ATAC sequencing datasets.
• Experience building single-cell reference atlases and integrating multi-modal biological datasets.
• Advanced proficiency in Python and bioinformatics or data science workflows.
• Experience working with high-performance computing or cloud computing environments for large-scale omics data analysis.
• Strong understanding of cell type annotation, clustering, trajectory inference, and regulatory network analysis.
• Excellent analytical, documentation, problem-solving, and communication skills.
• Ability to independently design, execute, and troubleshoot computational pipelines.

Preferred Qualifications:

• Experience with NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn.
• Familiarity with TensorFlow or PyTorch.
• Experience using Git for version control and collaborative software development.
• Hands-on experience with Scanpy, Seurat, Bioconductor, or comparable single-cell analysis platforms.
• Experience with multi-modal technologies such as CITE-seq, spatial transcriptomics, or chromatin accessibility analysis.
• Knowledge of regulatory network inference, peak-to-gene linking, and systems immunology.
• Experience developing artificial intelligence or machine learning models integrating transcriptomic, proteomic, and imaging datasets.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time, hours of paid vacation time, weeks of paid parental leave, and paid holidays annually – as applicable.

Pay Range: $50/hr to $55/