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Data Scientist/Biostatistician Global MSAT

Framingham, Massachusetts, Lyon, France, Vitry-sur-Seine, France, Gentilly, France



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"At Sanofi, We are guided by a deep appreciation and understanding of what it means to live with a rare blood disorder, and we learn by listening to the community – patients, caregivers physicians, and other healthcare professionals."

Shannon Resetich US Head Rare Diseases & Blood Disorders

"Patients are at the center of all that we do at Sanofi. Our teams are focused on advancing transformational therapies that can address serious unmet needs for people living with rare blood disorders, and expanding global patient access to our medicines."

Mouhamed Gueye US Head Medical Rare Blood Disorders



Within the Global MSAT Digital department, we are looking for an experienced Data Scientist / Biostatistician to join our Process Data Science group. 

The proposed position is based in Framingham, MA, and is to provide advanced data analytics, statistics, and process modeling support across multiple functions of Cell Culture, Purification and Analytical. 

This is an exciting opportunity to demonstrate the benefits of data science in a cutting-edge scientificdepartment and to contribute to the ambitious digital roadmaps. 


Global Manufacturing Sciences and Technology (MSAT) is a center of excellence in manufacturing and process sciences and as such is the keeper of the body of manufacturing process knowledge. It is a multi-disciplinary function that provides expertise in process and analytical sciences; manufacturing sciences, process modeling, trending and statistical analysis; process validation and technology transfer. 

The Global MSAT organization is the seeding ground for technical and scientific talent that executes their work in matrix organization. Furthermore, Global MSAT is providing cross-functional training and development and is the portal for collaboration with many different organizations including process development and operations. 

In that scope, Global MSAT is responsible for: 

  • Providing on-the-floor technical and scientific support.

  • Providing expertise in process/product-related investigations 

  • Overseeing and leading data management, monitoring and statistical analysis 

  • Owning technical transfers and process validation 

  • Defining and maintaining the product control strategy 

  • Owning comparability and product characterization 

  • Identifying commercial process/product life cycle improvements 

  • Identifying and driving implementation of improvements to maximize throughput and capacity utilization 


  • The MSAT Digital team is responsible for the roadmaps, deployment, and support for manufacturing process data analytics, lab automation, and digital transformation 

  • The group supports digital initiatives at the Industrial Affairs (IA) level and within IA-Specialty Care operations 

  • The group has capabilities in process statistics, operational modeling, and process design/cost analysis and will work collaboratively with process modeling/monitoring teams in the drug substance and drug product space 

  • It will also coordinate with data stewards on the Technical Product Teams 

  • Beyond these core focus areas, the group seeks to enhance digital ways-of-working across the MSAT organization 


  • Daily support of non-clinical statistical analysis and data modeling that contributes to the overall MSAT goals; offer proactive advice, service, and technical expertise upon request, to guarantee the reliability of statistical analyses. 

  • Solid understanding and use of statistical principles and practices to solve a range of complex problems in order to improve manufacturing success rates in real-time, provide retrospective data analysis for process improvements, and provide input for complex manufacturing investigations. 

  • Set up and analyze experimental studies. 

  • Perform process and data analysis for annual product reviews (APR) and periodic SPC reviews and support process investigations. 

  • Deliver training on statistical concepts. 

  • Co-author, review and/or approve procedures, protocols and reports containing significant statistical content with minimum supervision.

  • Contribute to the development and implementation of Process Data Analysis Tools (PDAT) 

  • 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. 

  • Develop or adapt to 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, regulations and guidance published by FDA, ICH, EMA and other regulatory groups, 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. 

  • Maintain, update, and communicate documentation and knowledge of statistical methods and techniques. 


  • Minimum Bachelor’s degree is required, preferably in one of the following disciplines: data sciences, statistics,bio-informatics or a similar field of study

  • A minimum 5 years' pharmaceutical industry experience

  • Experience developing data analytics solutions preferably on biologics processes 

  • Master statistical techniques, complex statistical analyses, data configuration and/or data modeling techniques 

  • Experience with statistical and database management software such as JMP, R, Python,Statistica, MATLAB,SIMCA, SQL, Oracle, etc. 

  • Fluent in English 


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

  • Work autonomously  

  • Excellent oral and written communication skills  

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


  • Master’s degree or PhD in data sciences, statistics, or a related discipline with minimum 5 years of experience in pharmaceutical industry 

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

  • Experience in leading complex technical substantive projects 

  • Experience in mentoring or training colleagues 

As a healthcare company and a vaccine manufacturer, Sanofi has an important responsibility to protect individual and public health. All US based roles require individuals to be fully vaccinated against COVID-19 as part of your job responsibilities.

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.




At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.

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