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Contenu de l'offre Data Scientist M/F chez Sanofi
Le site du Trait en Normandie produit des seringues pré-remplies de médicament à destination d’un large public. Notre ambition est de renforcer notre position d’usine injectable faisant partie des plus performantes d’Europe de l’Ouest.
Le site a concrétisé sa démarche de diversification en relevant le défi du lancement de 3 nouveaux produits injectables issus de la biotechnologie.
Les pathologies que nous traitons ? Les thromboses veineuses, phlébites et l’infarctus du myocarde.
Le contenu du poste est libellé en anglais car il nécessite de nombreuses interactions avec nos filiales à l’international, l'anglais étant la langue de travail.
JOB PURPOSE
Within the MSAT Digital organization, we are looking for an experienced Data Scientist to join our Process Data Analytics team
The position is based in our Pre-Filled Syringe (PFS) Centre of Excellence at LeTrait, France site, and is to manage the development and design of automated systems as well as to provide advanced analytics and system modeling support across multiple functions of Drug Product (fill and finish) and Analytics
Key linker to ensure end-to-end (E2E) data connectivity between the Specialty Care Drug Substance and Drug Product domains is available, providing data-driven insights for stakeholder review and decision-making
Liaise across the IASC MSAT drug product network sites, component suppliers and CMO partners on MSAT Digital roadmap initiatives of mutual interest
This is an exciting opportunity to demonstrate the benefits of system modeling and data science in a cutting-edge scientific department and to contribute to the ambitious MSAT site digital roadmap
GLOBAL MSAT FUNCTION DESCRIPTION
Global Manufacturing Sciences Analytical and Technology (MSAT) is a centre 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 a matrix organization. Furthermore, Global MSAT is providing cross-functional training and development and is the portal for collaboration with many different organizations including R&D, CMC, process development and Industrial Affairs 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, compliance monitoring and statistical analysis
Owning technical transfers resulting in right first time 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
MSAT DIGITAL DEPARTMENT DESCRIPTION
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 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
KEY ACCOUNTABILITIES
Daily support of statistical analysis and data modeling; offer proactive advice, service and technical expertise upon request, to guarantee the reliability of statistical analyses and/or automated systems
Configure and maintain Process Data Analysis Tools (PDAT)
Build expertise in state of the art process sensors
Monitor the performance of the tools used for data collection, data configuration, data storage / backup and recovery, 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
Ensure Data integrity tools are state of the art, e.g. audit trails monitor critical activities and produce simplified reports for rapid review
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
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
Collect, analyze and interpret data and analyses for reports
Maintain, update and communicate documentation and knowledge of statistical methods and techniques
Contribute to the transfer of knowledge and ensure the traceability and correctness of collected data
Ensure correct and timely information exchange with all relevant stakeholders
Mature Digital and Data Science skill levels for Drug Product SMEs so that digital solutions are leveraged to their optimal levels
PROFILE
Master’s degree or PhD in data sciences, computer sciences or a related discipline with minimum 5 years of experience in pharmaceutical industry
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets, including system modelling
Experience developing data analytics solutions on biopharmaceutical processes
Master statistical techniques, complex statistical analyses, data configuration and/or data modeling techniques
Domain knowledge in Biopharmaceuticals with direct experience in drug product development or manufacturing relevant to Pre-Filled Syringe device manufacture, testing and packaging
Lead complex technical substantive projects
Team player, ability to work effectively in a highly collaborative and dynamic environment across multiple sites
Change agent mentality, proposing novel approach to challenging scientific questions
Act as a mentor / coach / trainer to colleagues
Work autonomously
Excellent oral and written communication skills
Fluent in French and English; some fluency in German would also be an advantage
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.
As part of its diversity commitment, Sanofi is welcoming and integrating people with disabilities.