Process Data Lead

• Location: Geel, Belgium

About the job

Sanofi Global MSAT (Manufacturing Sciences, Analytics and Technology) acts as a crucial link between our R&D and Manufacturing facilities, playing a vital role in securing the present portfolio and delivering future launches of high-quality and innovative drugs and vaccines. By driving its own transformation, Global MSAT fulfills an important function by providing day-to-day Manufacturing Support, focusing on technical and process aspects, effective Life Cycle Management, process robustness enhancement, and yield improvement to optimize performance.

Under the lead of MSAT and in partnership with many other functions (Manufacturing 4.0, Digital, M&S, R&D), the MSATProcess Data Science & Digital Transformation team (MSAT DSD team) reaches operational excellence in process development, optimization & sustainability by putting in place a true data driven organization. As one Team, MSAT DSD organization is the data/digital DNA within the processes allowing us to ensure best in class manufacturing & analytical processes focusing on data/digital innovations & excellence aiming at guaranty acceleration/securitization launches & improvement/sustainability for our current processes.

Within the MSAT DSD department, the MSAT DSD Recombinant DS (Drug Substance) Platform, in particular for Immunology area, accelerates digital transformation for MSAT Recombinant Drug Substance Platform and supports current and new products (launch) by Data Science and Digital innovations.

Reporting to the Head of Immunology cluster within the MSAT DSD Recombinant DS Platform, the Process Data Lead will be responsible to obtain process data by connecting to a variety of source data systems and compiling the data into contextualized data sets to support process monitoring and key process-related decisions. This includes developing, implementing, and maintaining the necessary databases and applications.

The Process Data Lead will provide support for the internal customers: MSAT USP (UpStream Process), MSAT DSP (DownStream Process) and MSAT Analytics. The Process Data Lead will also be connected with other MSAT DSD people, in particular with the Process Data Management ML and AI platform, for harmonization, improvement, …

The Process Data Lead will have occasional business trips to other Sanofi Recombinant DS sites: Vitry-sur-Seine, Lyon Gerland, Frankfurt and Framingham.

Main responsibilities:

• undefined

• Assist in designing, developing, and maintaining data pipelines for manufacturing processes.

• Participate in data architecture and visualization projects to support manufacturing decision-making.

• Support the digital transformation of manufacturing processes through data-driven solutions.

• Support and develop MSAT data pipeline (ETL).

• 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/development, validation and/or maintenance of MSAT computerized systems/applications.

• 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 (for example, for yields improvement); offer proactive advice, service and technical expertise upon request, to guarantee the reliability of data analyses and/or automated systems.

About you

• Master’s Degree or PhD in Data Science, Data Engineering, Computer Science or in a related discipline, with minimum 5 years of experience in industrial statistics.

• Fluent in French and in English.

• Rigorous, dynamic, pedagogue and autonomous.

• Strong communication and teamwork abilities.

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

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

• Excellent problem-solving skills and attention to detail.

• Strong interest in data engineering and analytics, particularly in manufacturing contexts.

• Knowledge of Python programming, SQL and database concepts, cloud platforms (particularly Snowflake), Dataiku.

• Good understanding of version control systems, especially GitHub.

• Experience in pharmaceutical manufacturing processes and quality control.

• Experience working in GxP environment and extensive knowledge of regulatory guidelines.

• Skills in data configuration, statistical data analysis and/or data modeling techniques.

• Experience in leading complex technical substantive projects.

Why choose us?

• Bring the miracles of science to life alongside a supportive, future-focused team

• Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally

• Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave

• Play an instrumental part in creating best practice within our manufacturing facility

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