For our Client Hoffman La-Roche we are looking for a motivated

Temporary R&D Data Scientist

Location: Basel, Switzerland

Workload: 100%

Contract Duration: 12 months (maternity leave cover)

Start Date: ASAP

Home Office: Hybrid (≥50% on-site required)

About the Role

Roche is seeking a skilled, hands-on Temporary R&D Data Scientist to support our Research & Development data operations during a maternity leave period. In this role, you will ensure continuity of our data integration workflows, contribute to ongoing AI/ML development, and help maintain the backbone of our data-driven research activities.

This is an opportunity for a technically strong, autonomous data scientist who can quickly adapt to complex scientific datasets and take ownership of critical pipelines and analysis tasks from day one.

Key Responsibilities

Data Integration & Pipeline Management

• Maintain, monitor, and troubleshoot existing ETL and data integration pipelines supporting AI/ML workflows.
• Ensure data quality, reproducibility, and uptime across R&D platforms.

AI & Machine Learning Support

• Assist in training, validating, and optimizing machine learning models used for scientific research.
• Collaborate with data scientists, engineers, and researchers to enhance performance and reliability.

Data Analysis & Reporting

• Conduct exploratory and statistical analyses to support research questions.
• Deliver clear reports, visualizations, and summaries to cross-functional partners.

Technical Problem-Solving

• Diagnose issues in data access, tooling, and model performance.
• Propose and implement solutions with minimal supervision.

Documentation & Continuity

• Maintain structured, clear documentation of pipelines, code changes, and workflows.
• Ensure smooth project continuity during and after the temporary contract.

Must-Have Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Bioinformatics, or related field.
• 3–5+ years of hands-on experience in a data science or data analytics role.
• Strong Python skills, including Pandas, NumPy, scikit-learn.
• Proficiency in SQL and working with relational databases.
• Experience working with ETL processes and pipeline orchestration.
• Foundational understanding of machine learning concepts and model evaluation.
• Experience with image analysis (microscopy, biomedical, or computational imaging).
• Ability to work independently in a fast-paced scientific environment.
• Excellent communication skills and collaborative mindset.
• Understanding of FAIR Data Principles.

Nice-to-Haves

• Experience in pharma, biotech, or research environments.
• Exposure to multi-omics, microscopy, or biological R&D datasets.
• Familiarity with cloud computing or pipeline orchestration frameworks.