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Bioinformatics Analyst III
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Actalent
Remote
$124,800 Salary, Full-Time
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Job Description
Job Title:
Bioinformatics Analyst III Job Description This role focuses on analyzing large-scale single-cell transcriptomic and epigenomic datasets to advance single-cell atlas initiatives within an immunology discovery context. You will build high-quality reference maps, define tissue-specific niches, and uncover their roles in health and disease by leveraging advanced computational, AI/ML, and bioinformatics workflows. The position requires close collaboration with cross-functional scientific teams and clear communication of complex scientific results. Responsibilities Curate, harmonize, and analyze large-scale scRNA-seq and scATAC-seq datasets from both internal and public sources. Integrate multi-modal data to support the construction and refinement of comprehensive single-cell atlases. Develop and apply computational and AI/ML methods to classify cell states, identify regulatory networks, and generate disease-relevant insights. Support interpretation of model outputs to deepen understanding of cell-state biology, tissue-specific function, and fibroblast heterogeneity. Collaborate with immunology, computational, and cross-functional stakeholders to translate biological questions into robust computational solutions. Design, implement, and maintain reproducible data curation, processing, and analysis pipelines, ensuring thorough documentation and transparency. Independently design, execute, and troubleshoot computational workflows for large-scale omics datasets. Contribute to time-sensitive projects that support target discovery and validation in immunology and related areas. Communicate scientific findings and analytical results clearly to both technical and non-technical audiences. Adhere to best practices for version control, code review, and collaborative development in computational biology projects. Essential Skills MS degree with 5 years of experience or PhD with 0 years of experience in a quantitative field such as Bioinformatics, Computational Biology, Computer Science, Computational Genetics, Biostatistics, AI/Machine Learning, or a related discipline. Experience analyzing single-cell transcriptomics and epigenomics data, particularly scRNA-seq and scATAC-seq. Experience with single-cell atlas construction and multi-modal data integration. Strong proficiency in Python and standard machine learning and data science libraries. Experience working in high-performance computing (HPC) or cloud environments for large-scale omics datasets. Domain knowledge in single-cell analysis, chromatin accessibility analysis, or systems immunology. Familiarity with cell type annotation, clustering, trajectory inference, and regulatory analysis. Ability to independently design, execute, and troubleshoot computational workflows. Strong attention to detail, including rigorous documentation and clear scientific communication. Ability to communicate scientific results clearly and work collaboratively across interdisciplinary teams. Additional Skills & Qualifications Experience with Python scientific and data science libraries such as NumPy, scikit-learn, Matplotlib, and Seaborn. Familiarity with deep learning frameworks such as TensorFlow and/or PyTorch. Proficiency with Git for version control and collaborative software development. Hands-on experience with single-cell analysis tools, including popular Python or R/Bioconductor ecosystems. Exposure to multi-modal integration methods such as CITE-seq, ATAC-seq, or spatial transcriptomics. Experience with cell type annotation, clustering, and trajectory inference in single-cell datasets. Knowledge of regulatory network inference and peak-to-gene linking approaches. Experience building multi-modal AI/ML models that connect transcriptomic, proteomic, and imaging data. Strong problem-solving skills and the ability to translate complex biological questions into computational analyses. Work Environment You will work in a highly collaborative, research-driven environment focused on immunology discovery and target identification. The role involves extensive use of Python, standard machine learning and data science libraries, and single-cell analysis tools, supported by high-performance computing (HPC) and cloud-based infrastructures for large-scale omics data. You will collaborate closely with immunologists, computational scientists, and cross-functional partners, contributing to time-sensitive projects that drive scientific and therapeutic insights. The work setting emphasizes reproducibility, transparent documentation, and modern software development practices such as version control with Git. Dress expectations align with a professional research and technology environment. Job Type & Location This is a Contract position based out of Cambridge, MA. Pay and Benefits The pay range for this position is $58.00 - $62.00/hr. Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:- Medical, dental & vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life & AD&D for the employee and dependents)
- Short and long-term disability
- Health Spending Account (HSA)
- Transportation benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type This is a fully remote position.