Data Scientist
Role Overview
Genomics combines large-scale genetic and health data with proprietary analytics to accelerate drug discovery and predictive, preventative healthcare.
The Data Scientist develops and integrates support for processing, quality control, and analysis of new data types into production and research software tools.
The role combines genetics expertise, data analysis, statistical methods, and software engineering.
Key Skills for This Role
Full Job Posting
Location and working model
- The role can be based in Oxford or London and is described as hybrid.
- The working environment includes London and Oxford offices.
Mission and role purpose
Genomics combines large-scale genetic and health data with proprietary analytics to accelerate drug discovery and predictive, preventative healthcare.
The Data Scientist develops and integrates support for processing, quality control, and analysis of new data types into production and research software tools.
The role combines genetics expertise, data analysis, statistical methods, and software engineering.
Core responsibilities
- Identify new uses of functional genomics, perturbation screens, molecular profiles, expression atlases, annotations, pathways, and interaction resources.
- Implement production-quality processing, transformation, and quality-control code for new data types.
- Contribute to robust, validated, and reproducible statistical and machine learning methods.
- Contribute to presentations and publications and maintain current genomics and statistical genetics knowledge.
Senior-level scope
- At IC3 level, lead projects integrating multiple functional genomics and genetic data sources.
- At IC3 level, coordinate with cross-disciplinary teams to deliver value.
Essential qualifications
- Strong human genetics and functional or clinical genomics knowledge applied to research questions.
- Skill analysing large-scale biological datasets with statistical and machine learning methods.
- Experience processing and interpreting functional genomics and related biological resources, including quality control.
- Competence writing Python and/or R for data analysis with awareness of good software development practice.
Preferred qualifications
- Appropriate use of LLM programming assistants in research analysis.
- Experience with scalable Linux HPC or cloud workflows, collaborative codebases, version control, and CI/CD.
- Experience with remote cloud environments such as AWS.
- Prior team or industry experience.
- PhD or postgraduate degree in a relevant genetics, genomics, computational biology, bioinformatics, statistics, or machine learning field.
Compensation and growth
- The employer describes externally benchmarked competitive salaries, a clear progression framework, and continuous learning resources.
Wellbeing and time off
- Benefits include holiday allowance, company shutdown, pension, private health insurance, critical illness and life assurance, and enhanced paid family leave.
Culture and environment
- The company describes inclusive working practices, flexible hybrid work, social activities, and cycle-to-work support.
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