Senior Bioinformatics Analyst/ Computational Biologist

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/