Associate Director, Translational Data Sciences
$82,500–$137,500 year
On-siteHeidelberg, Baden-Wurttemberg, Germany or Upper Providence, Pennsylvania, United States
Job Summary
Lead design, delivery, and interpretation of translational analyses using genetics, genomics, proteomics, and clinical phenotypes to inform target, biomarker, and patient-selection decisions. Own end-to-end analytical workstreams including data ingestion, quality control, analysis, and reproducible pipelines, while translating scientific questions into robust computational approaches for diverse stakeholders. Partner with AI/ML, platform, and bioinformatics teams to operationalize methods in secure computing environments, and mentor scientists and analysts to build team capacity. Deliver reproducible, well-tested analytic pipelines for large-scale datasets and ensure analyses meet data governance, privacy, and traceability standards. Represent the team in cross-functional programme meetings and external collaborations when needed.
Required Qualifications
- Physical sciences (Maths, Computer Science, Physics, Chemistry, Engineering etc) or Biological sciences (Biology, Biochemistry, Bioengineering etc) undergraduate degree or Medical degree
- PhD in data science, computer science, computational biology, bioinformatics, or a closely related discipline
- Hands-on experience analysing large-scale genetic and multi-omics datasets and integrating these with clinical or phenotypic data
- Strong programming skills in Python
- Experience delivering reproducible, production-quality analysis (version control, testing, documentation)
- Experience building or owning end-to-end analytic pipelines and workflows in a research or R&D setting
- Clear written and verbal communication skills with experience presenting technical results to non-specialist stakeholders
- Ability to work effectively in multidisciplinary teams and to manage competing priorities
- Must be able to lift 50 lbs
Desired Qualifications
- Experience in translational settings within pharma, biotech or clinical research, with track record of influencing project decisions
- Familiarity with machine learning or advanced statistical methods applied to molecular or clinical data
- Experience working with single-cell, spatial, proteomic or other emerging omics modalities
- Experience with cloud platforms, trusted research environments or scalable compute systems
- Track record of peer-reviewed publications, presentations or external collaborations
- Experience leading small teams, mentoring staff, or coordinating cross-functional projects
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