Data Scientist – Translational Research (7149)

Join a Global Leader in Pharmaceutical Innovation

Partner with a leading global pharmaceutical organization headquartered in Basel, Switzerland, that is undergoing a significant transformation in culture and external perception. This organization focuses on novel therapies in Oncology and Ophthalmology while developing a world-leading pipeline in Neuroscience and Dermatology, boasting one of the strongest portfolios of Phase II/III studies globally.

As a specialized search and recruitment partner for the Life Sciences industry since 1997, we connect talented professionals with meaningful opportunities. We are currently seeking a dedicated professional to join this transformative team on a six-month contract basis in Basel.

Key Responsibilities

• Approach multi-modal clinical data to identify biomarkers predictive of disease progression and treatment response, and nominate novel therapeutic target hypotheses.
• Develop and apply a portfolio of pre-clinical models derived from internal and public data to departmental projects.
• Collaborate closely with a core team of Translational Research and Data Science scientists fluent in both wet and dry lab practices.
• Actively participate in interdisciplinary teams to model biology and guide impactful decision-making.
• Build alliances with external partners at top healthcare institutions.

Required Profile

• Relevant working or residency permit, or Swiss/EU citizenship.
• Demonstrated working knowledge and application of statistics and data modeling to large-scale life-sciences data.
• Proficiency in R/Python and competency working in a Linux environment.
• Hands-on experience applying AI and machine learning methods to scientific or R&D data, including large language models and agentic workflows.
• Hands-on experience in the integration of large multi-omics data (genomics, transcriptomics, proteomics, and metabolomics) to answer key scientific questions related to understanding disease.
• Hands-on expertise across transcriptomics, genetics, and proteomics, including single-cell and bulk RNA-seq, spatial transcriptomics, CITE-seq, CyTOF, and imaging mass cytometry.
• Hands-on industry experience modeling biomedical research data.
• Strong communication skills in English.
• Experience working with or fine-tuning foundation models in biology, chemistry, or clinical data (desirable).