Recursion - Senior Computational Biologist, Tooling
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Requirements
• PhD in a relevant field (e.g., computational biology, bioinformatics, statistics, quantitative pharmacology, cancer/cell biology, computer science, or a related discipline), or equivalent experience, with a track record of applying these skills to fundamental problems in drug discovery. • Experience applying computational methods (including statistical, probabilistic, and/or machine learning techniques) to analyse complex biological and/or human clinical data. • Experience building, maintaining, and improving reproducible data pipelines and analytical workflows for large, heterogeneous biological datasets (Python strongly preferred). • Experience working with high-dimensional biological datasets, including omics data (e.g., single-cell and other genomics-based modalities) and/or other complex assay modalities. • Experience turning exploratory analyses into reusable tools, workflows, and documentation that can be adopted by other scientists/teams. • General understanding of drug discovery and translational biology. • Experience working on highly collaborative cross-functional teams; ability to clearly explain computational analyses, data workflows, and methodologies to cross-functional and non-technical teams. • Hands-on experience working with real-world clinical datasets (EHR/claims/registries) and/or generating real-world evidence (cohorting, endpoint definition, observational study considerations). • Experience with real-world clinical datasets (e.g., EHR-derived oncology datasets) or demonstrated ability to rapidly learn new healthcare data modalities; experience with Tempus or similar datasets is a plus. • Experience integrating multimodal datasets (e.g., genomics + phenomics, genomics + imaging) in service of translational decisions. • Experience developing or applying agentic workflows to orchestrate analyses across multiple internal and external data sources, accelerating insight generation and decision-making
Responsibilities
• Synthesize, integrate, and analyse diverse internal and external datasets from computational biology, target discovery, functional genomics, biomarker discovery, and real-world and clinically derived data sources, and identify commonalities to turn into reusable tools and pipelines. • Synthesize • Build, maintain, and improve robust data pipelines and analytical workflows for complex biological datasets, including omics data, internally generated biological assay data, and external data sources such as Tempus and other real-world datasets. • Build, • Develop and apply agentic workflows to integrate and orchestrate analyses across multiple internal and external data sources, accelerating insight generation and supporting scalable decision-making across drug discovery programs. • Develop • Partner with engineers to mature pilot tooling and workflows into stable products and infrastructure that multiply the effectiveness of scientific collaborators pursuing drug programs. • Partner • Present and discuss data, pipelines, and tools with decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients. • Present • Collaborate cross-functionally with Recursion’s platform data science, data engineering, and ML teams to further advance Recursion’s ability to interpret and translate large-scale phenomics and multimodal data into therapeutic programs. • Collaborate
Benefits
• This is an office-based, hybrid position at our office located in London, England. Employees are expected to work in the office at least 50% of the time. • London, England.
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