Senior Biological Data Scientist
New
J
JobgetherBiotechnology
Remote U.S.-based positionFull-TimeSenior
Salary$155,000 to $205,000 per year
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Job Details
- Experience
- 5+ years of industry and/or postdoctoral experience
- Required Skills
- PythonData science
Requirements
- PhD in Computational Biology, Bioinformatics, Genetics, or a related quantitative discipline.
- 5+ years of industry and/or postdoctoral experience working with large-scale biological datasets.
- Proven expertise integrating transcriptomic, proteomic, genomic, and other multiomics data to solve complex biological research questions.
- Experience supporting biomarker discovery, translational research, target identification, or drug discovery within biotechnology or pharmaceutical environments.
- Strong programming skills in Python for scientific computing, statistical analysis, and data processing.
- Experience applying computational biology techniques to unfamiliar disease areas through effective data integration and hypothesis generation.
- Excellent communication and collaboration skills with the ability to work independently in a fast-moving scientific environment.
- Familiarity with single-cell RNA sequencing, spatial transcriptomics, or other advanced cellular profiling technologies (preferred).
- Familiarity with large language models, AI-assisted research workflows, and computational biology applications leveraging modern AI technologies.
Responsibilities
- Design, execute, and interpret integrative computational analyses across transcriptomic, proteomic, genomic, and other biological datasets to support therapeutic discovery and translational research.
- Integrate internal and publicly available multiomics data to identify, prioritize, and refine therapeutic targets, biomarkers, and mechanism-of-action insights.
- Apply advanced computational methods and AI-enabled tools to accelerate biological discovery while ensuring scientific rigor and validation.
- Collaborate closely with cross-functional research teams to translate complex computational findings into actionable scientific strategies.
- Communicate research outcomes through presentations, technical reports, scientific publications, and conference contributions.
- Continuously evaluate emerging computational methodologies and biological datasets to strengthen research capabilities and accelerate innovation.
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