INT-122493 21.10.2026

Data Scientist

Bâle
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Pharmaceutique / Biotechnologies / Chimie
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Temporaire - Temps partiel

Flexsis is a company of the Interiman Group, one of the leading providers of personnel services in Switzerland. Thanks to our solid expertise as well as the competencies within the Interiman Group, we offer tailored solutions in personnel consulting.

For our client Novartis in Basel, we are looking for a reliable and motivated Data Scientist (m/f/d)

Duration: 6 month - maternity cover

Workload: 80%

Description de la mission

Key Responsibilities:

Applying established and novel approaches to model multi-modal clinical data to identify biomarkers predictive of disease progression and treatment response, and to nominate novel therapeutic target hypotheses
Developing and applying a portfolio of pre-clinical models derived from internal and public data to departmental projects
Working closely with a core team of Translational Research & Data Science scientists fluent in wet and dry lab practices
Actively participating on interdisciplinary teams to model biology and guide impactful decision-making in drug discovery and early development
Actively participating in alliances with external partners at top healthcare institutions, including the opportunity to publish your findings

Essential Requirements:

Life sciences industry experience modeling biomedical research data
Demonstrated working knowledge and application of statistics and data modeling to large scale life-sciences data • Hands-on experience in integration of large multi-omics data (genomics, transcriptomics, proteomics and metabolomics) to answer key scientific questions related to understanding disease
Hands-on industry experience with clinical data and its responsible handling
Hands-on experience applying AI and machine learning methods to scientific or R&D data
Experience using AI tools, including large language models and agentic workflows, to accelerate analysis and decision-making
Proficiency in R/Python and competency working in a Linux environment
Reproducible research practitioner with demonstrated visualization and reporting skills
A team-oriented, practical approach to problem solving

Profil attendu pour l'emploi

Must haves:

Working knowledge and application of statistics and data modeling to large scale life-sciences data
Hands-on experience in integration of large multi-omics data (genomics, transcriptomics, proteomics and metabolomics) to answer key scientific questions related to understanding disease
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.
Experience using AI tools, including large language models and agentic workflows, to accelerate analysis and decision-making.