• Location: Geel

• Job type: Permanent

• Travelling: sporadically, up to 10% travel

About the job

The MSAT Data Engineer 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 MSAT DSD Data Science Recombinant 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.

The proposed position is to manage the development and design of automated systems as well as to provide advanced analytics across multiple functions of Cell Culture, Purification and Analytics.

Main responsibilities:

• Monitor the performance of the tools used for data collection, data configuration, data analysis and/or data modeling; and adjust and/or escalate where necessary, to prevent deviations from standards, resolve bottlenecks and identify opportunities for improvement to meet the predefined quality requirements.

• Contribute to the configuration, validation and/or maintenance of MSAT computerized systems.

• Represent MSAT by advocating for the needs of the organization within the existing and future digital tool landscape.

• 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 or adapt existing and innovative methods and techniques for data collection, data configuration, data analysis and/or data modeling, to continuously increase effectiveness and efficiency of relevant statistical methods and 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.

• Collect, analyze and interpret data and analyses for reports. Ensure the traceability and correctness of collected data. Ensure correct and timely information exchange with all relevant stakeholders.

• 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.

• Contribute to (statistical) data analysis and data modeling; offer proactive advice, service and technical expertise upon request, to guarantee the reliability of data analyses and/or automated systems.

• Contribute to design of necessary experiments and to interpretation of results; recommend changes or additional experiments.

About you

Basic qualifications:

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

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

• Ph.D. in data sciences, computer sciences 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

• Experience developing data analytics solutions on biologics processes

• Master data configuration, (statistical) data analysis and/or data modeling 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