Principal Scientist - Statistical Genetics

13th October, 2026

Principal Scientist – Human Genetics
Cardio-Renal-Metabolic
Location : Germany | Hybrid

If you’re a Human Geneticist who enjoys turning complex population-scale data into decisions that actually shape drug discovery, this could be a very interesting next move.

We’re supporting a major global pharmaceutical R&D organisation that is looking for a Principal Scientist in Statistical Genetics to join a highly collaborative disease genetics team in southern Germany.

The focus is on the cardio-renal-metabolic space, so this role would suit someone with strong statistical genetics expertise alongside genuine disease knowledge across areas such as cardiovascular disease, kidney disease, obesity, diabetes, liver disease or related metabolic disorders.

This is not a role where you simply generate analyses and hand them over.
You’ll be expected to take complex genetic evidence, challenge assumptions, form a point of view and help influence decisions around targets, indications, mechanisms, biomarkers, patient stratification and safety.

What you’ll be working on

• Using population-scale biobanks, clinical cohorts and longitudinal datasets to support discovery and portfolio decisions
• Identifying and prioritising genetically supported targets and indications
• Applying approaches such as GWAS, PheWAS, fine-mapping, colocalisation, Mendelian randomisation, rare-variant analysis, polygenic risk scores and time-to-event analysis
• Integrating genetics with QTL, transcriptomic, proteomic, single-cell and other functional datasets
• Investigating causal genes, mechanisms, relevant cell types and disease subtypes
• Building evidence packages that inform target selection and key programme milestones
• Translating complex genetic findings into clear recommendations for multidisciplinary drug discovery teams
• Working closely with therapeutic-area, experimental, translational, clinical, data and computational scientists
• Contributing to external scientific collaborations and helping improve shared genetics workflows and standards
• At Principal level, there is more emphasis on scientific ownership and leadership.
• You’ll be expected to independently define genetics strategy for complex portfolio questions, lead ambiguous workstreams from initial problem framing through to decision, and act as a senior scientific voice in portfolio discussions.
• You’ll also help set quality standards, review the work of other scientists and contribute to the development of scalable and potentially AI-enabled genetics workflows.

What we are looking for

• A PhD in Statistical Genetics, Genetic Epidemiology, Bioinformatics, Computational Biology, Statistics, Computer Science or a related field
• Post-PhD experience in pharma or biotech (5 years+)
• Strong experience applying human genetics to drug discovery or development
• Deep knowledge of at least one major cardio-renal-metabolic disease area
• Experience working with biobank-scale and longitudinal datasets
• Strong statistical genetics capability
• Good programming skills in R and/or Python
• Experience working in reproducible analysis environments
• The ability to communicate complex evidence clearly and influence decisions across multidisciplinary teams
• Experience leading projects and managing multiple scientific stakeholders
• Demonstrated scientific leadership, can operate independently in complex programmes and are comfortable challenging senior stakeholders when the evidence points in a different direction.