R&D Data Steward Manager Associate

About the job

Sanofi is a global life sciences company committed to improving access to healthcare and supporting the people we serve throughout the continuum of care. From prevention to treatment, Sanofi transforms scientific innovation into healthcare solutions, in human vaccines, rare diseases, multiple sclerosis, oncology, immunology, infectious diseases, diabetes and cardiovascular solutions and consumer healthcare. More than 110,000 people in over 100 countries at Sanofi are dedicated to making a difference on patients’ daily life, wherever they live and enabling them to enjoy a healthier life.

As a company with a global vision of drug development and a highly regarded corporate culture, Sanofi is recognized as one of the best pharmaceutical companies in the world and is pioneering the application of Artificial Intelligence (AI) with strong commitment to develop advanced data standards to increase reusability & interoperability and thus accelerate impact on global health.

The R&D Data Office serves as a cornerstone to this effort. Our team is responsible for cross-R&D data strategy, governance, and management. We sit in partnership with Business and Digital, and drive data needs across priority and transformative initiatives across R&D. Team members serve as advisors, leaders, and educators to colleagues and data professionals across the R&D value chain. As an integral team member, you will be responsible for defining how R&D's structured, semi-structured and unstructured data will be stored, consumed, integrated / shared and reported by different end users such as scientists, clinicians, and more. You will also be pivotal in the development of sustainable mechanisms for ensuring data are FAIR (findable, accessible, interoperable, and reusable).

Position Summary:

The R&D Data Steward plays a critical role in the intersection between business and data, where stewards will guide business teams on how to unlock value from data. This role will drive definition and documentation of R&D data standards in line with enterprise. Data stewards will place heavily cross-functional roles and must be comfortable with R&D data domains, data policies, and data cataloguing.

Main responsibilities:

• Under the leadership of the Data Steward Manager, work in collaboration with the Lab Scientists from the Chemistry, Manufacturing & Controls department to ensure that data produced are Findable, Accessible, Interoperable and Reusable
• Work in collaboration with R&D Data Office leadership, Business Users, R&D Digital subject matter experts and other partners to:
  • Understand the data-related needs for various cross-R&D capabilities (E.g., data catalog, master data management etc) and associated initiatives
  • Design and document data governance policies, standards and procedures for R&D data
  • Drive data standard adoption across capabilities and initiatives; manage and maintain quality and integrity of data via data enrichment activities (E.g., cleansing, validating, enhancing etc)
  • Understand and adopt data management tools such as R&D data catalogue, etc
  • Develop effective data sharing artifacts for appropriate usage of data across R&D data domains
  • Ensure the seamless running of the data-related activities and verify data standard application from ingest through access
  • Maintain documentation and act as an expert on data definitions, data flows, legacy data structures, access rights models, etc. for assigned domain
  • Oversee data pipeline and availability and escalate issues where they surface; ensure on-schedule/on-time delivery and proactive management of risks/issues
  • Educate and guide R&D teams on standards and information management principles, methodologies, best practices, etc.

Deliverables:

• Accountable for data quality and data management activities for the CMC – Chemistry Manufacturing & Control - data domain
• Defines Data quality and communication metrics for the CMC – Chemistry Manufacturing & Control - data domain

• Implements continuous improvement opportunities such as functional training

• Facilitates data issue resolution

• Coordinates the definition of business terms and data elements (metadata) in close collaboration with business SME and according to industry standards whenever possible, to ensure standardization/normalization of metadata

• Leads working groups to identify data elements, perform root cause and impact analysis, and identify improvements for metadata and data quality

• Regularly communicates with other data leads, expert Data Stewards and escalates issues as appropriate

3. About you

• Experience: 5+ years in Business Data Management, Information Architecture, Technology, or related fields
  
• Functional skills:
  • Good knowledge in the Pharma R&D CMC – Chemistry Manufacturing and Controls domain.
  • Ability to understand data processes in the scientific laboratory context and requirements from Lab Scientist, as well as from Data Scientists analysing the CMC data. 
  • Demonstrated ability to communicate clearly with business users involved in data related activities: the data producers, the data owners and the data consumers
  • General knowledge of R&D data domains (e.g., across research, clinical, regulatory etc)
  • Solid grasp of data governance practices and track record of implementation
  • Demonstrated strong attention to detail, quality, time management and customer focus
  • Excellent written and oral communications skills
  • Strong networking and influencing skills and superior problem-solving skills
  • Demonstrated willingness to make decisions and to take responsibility for such
  • Excellent interpersonal skills (team player)
  • People management skills either in matrix or direct line function
• Technical Skills
  • Experience in data management and data stewardship in systems used in laboratories context: electronic Lab Notebook (eLN), Laboratory Information Management System (LIMS), Scientific Information Management Systems (SDMS), Laboratory Execution System (LES), …
  • Experience with data management practices and technologies such as:
    • data cataloguing
    • data modelling & ontology management
    • data quality frameworks
    • data wrangling and visualization tools with tools such Power BI, Dataiku, …
  • Agile mindset and practice
  • Knowledge of pharma R&D industry regulations and compliance requirements related to data governance

• Education: Bachelors in Computer Science, Business, Engineering, Information Technology
• Languages: English

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