Sanofi has over 110,000 employees, operates in more than 100 countries, and is thus one of the largest pharmaceutical companies in the world. Sanofi’s strengths include diabetes solutions, vaccines, innovative medicines, consumer health care, emerging markets, and animal health products.

Our Team:

The Data Scientist is a member of the Process Data Science Recombinant platform of the Data Science and Digital Transformation (DSD) team within the global Manufacturing Science, Analytics and Technology (MSAT) organization and is based in Sanofi Geel biopharmaceutical manufacturing site.

The Recombinant Mammalian DS platform function within global MSAT is the owner of Life Cycle Management of mammalian cell culture-based DS Processes within Sanofi biologics manufacturing network. We deliver innovative, robust, and cost-effective next generation processes, enable launch of new products, and provide commercial manufacturing/Quality Control support. The function is responsible for tech transfer activities including fit-gap assessment, validation, dossier sections preparation, & PAI support to enable launch of new and LCM products. Our expansive portfolio covers multiple products, modalities, and expression systems within 12 internal and external global sites in US and EU. We will be supporting launch of 20+ new products in next 3-5 years including monoclonal and multi-specific antibodies, fusion proteins, antibody-drug conjugates, synthorins and nanobodies. We are pursuing future innovations such as digital labs, factory of future and advanced analytics-based process understanding and control.

The team provides dedicated day to day support to manufacturing and process development of products supported by the MSAT Recombinant Drug Substance platform. We drive innovation, excellence and harmonization in Data Science areas, and act as Data Stewards in Technical Product Teams for all recombinant Drug Substance products.

Key accountabilities:

• The proposed position is to provide advanced Statistics and Data Science support across multiple MSAT functions of Cell Culture, Purification and Analytical.


• MSAT activities to support typically include, but are not limited to: process/method optimization/improvement, process/method investigation, comparability studies, process monitoring, method transfer/validation, small-scale model qualification and process characterization.


• Contribute to MSAT protocols and reports with significant statistical content by collecting data, designing experiments, and/or statistically analyzing and interpreting data. Offer advice, service and technical expertise, proactively and/or upon request, to guarantee the reliability of data analyses.


• Ensure the traceability and correctness of collected data. Ensure correct and timely information exchange with all relevant stakeholders.


• Follow up on developments within the domain of expertise as well as building and sharing knowledge within this domain, to translate these developments into accurate and relevant information and expert advice for the organization


• Develop innovative or adapt existing methods and techniques to continuously increase effectiveness and efficiency of relevant statistical methods and data analysis techniques to contribute to process improvement.


• Ensure proper compliance with legal standards and regulations, to contribute to high-quality scientific/technical reports and documents, and strive for optimal quality of methods/techniques in accordance with agreements, guidelines and regulations.


• Build and maintain a professional network, to increase and transfer scientific/technical knowledge and come to a substantiated, supported and integrated approach for relevant projects.

Basic qualifications

• BS in data sciences, statistics or a related discipline with at least 6 years of experience in pharmaceutical industry


• MS in data sciences, statistics or a related discipline with at least 4 years of experience in pharmaceutical industry


• Ph.D. in data sciences, statistics or a related discipline with at least 2 years of experience in pharmaceutical industry

Preferred qualifications

• Experience working in a cGMP environment and extensive knowledge of regulatory guidelines


• Master statistical data analysis and data science techniques


• Domain knowledge in Biologics with direct experience in either upstream or downstream development or manufacturing


• Lead complex technical substantive projects


• Team player, ability to work effectively in a highly collaborative and dynamic environment


• Change agent mentality, proposing novel approach to challenging scientific questions


• Act as a mentor to colleagues


• Work autonomously


• Effective communication skills (written and verbal) in Dutch and English with cross-functional teams and senior management