Bioinformatics Analyst

The ideal candidate has a strong background in computational biology, single-cell genomics, and Python-based data analysis. Working closely with immunologists, computational scientists, and cross-functional research teams, you will develop scalable computational workflows that generate insights supporting target identification and validation., * Curate, harmonize, and analyze large-scale scRNA-seq and scATAC-seq datasets from internal and public data sources.

• Build and support comprehensive single-cell atlas initiatives through multi-modal data integration.
• Develop and apply computational and AI/ML methods to classify cell states, identify regulatory networks, and generate disease-relevant biological insights.
• Perform cell type annotation, clustering, trajectory inference, and regulatory analyses to better understand tissue biology and cellular heterogeneity.
• Collaborate with immunology researchers and cross-functional scientific teams to translate biological questions into computational solutions.
• Design, execute, and optimize reproducible bioinformatics pipelines within HPC or cloud computing environments.
• Document data curation, processing, and analytical workflows to ensure reproducibility and transparency.
• Present findings and recommendations to scientific stakeholders while contributing to target discovery and validation efforts.

• M.S. degree with 5+ years of relevant experience, or Ph.D. in Bioinformatics, Computational Biology, Computer Science, Computational Genetics, Biostatistics, AI/Machine Learning, or a related quantitative discipline.
• Hands-on experience analyzing single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) datasets.
• Experience with single-cell atlas construction and multi-modal data integration.
• Strong programming skills in Python and standard data science libraries.
• Experience working with HPC clusters or cloud-based environments for large-scale omics data analysis.
• Strong analytical thinking, attention to detail, and excellent written and verbal communication skills.
• Ability to independently design, execute, troubleshoot, and document computational workflows.

Preferred Qualifications

• Experience with Scanpy, Seurat, Bioconductor, or similar single-cell analysis platforms.
• Knowledge of NumPy, Pandas, Scikit-learn, Matplotlib, TensorFlow, and/or PyTorch.
• Experience using Git for version control and collaborative software development.
• Familiarity with CITE-seq, spatial transcriptomics, chromatin accessibility analysis, or other multi-modal technologies.
• Experience with cell type annotation, clustering, trajectory inference, regulatory network inference, and peak-to-gene linking.
• Knowledge of systems immunology, fibroblast biology, or disease biology is a plus.
• Experience developing AI/ML models integrating transcriptomic, proteomic, imaging, or other multi-omics datasets is highly desirable.

Top Skills

• Single-cell transcriptomics and epigenomics (scRNA-seq, scATAC-seq)
• Single-cell atlas construction and multi-modal data integration
• Python and bioinformatics/data science workflows
• Cell type annotation, clustering, trajectory inference, and regulatory analysis
• Cross-functional collaboration and scientific communication

The Fountain Group is a national staffing firm and we are currently seeking a Bioinformatics Analyst for a prominent client of ours. This position is in Cambridge, MA 02142. Details for the position are as follows