Scientific Data Manager

Servier

Gif-sur-Yvette, France

We are seeking a Scientific Data Manager to join our Data Sciences & Data Management Unit. In this role, you will support Servier’s research pipeline by contributing to strategic data management projects, ensuring that our preclinical data is a trustable asset for life-changing therapeutic innovation.

Responsibilities:

Data Integrity & Standardization: Ensure data integrity within your assigned domain by implementing ALCOA++ and FAIR principles. Drive data quality through the implementation of Master Data Management (MDM) and scientific ontologies.
Business Partnership: Serve as a data referent for assigned projects, gathering and translating business and data science needs into actionable data management strategies.
Systems Management: Contribute to the administration and optimization of Drug Discovery information systems. Support applications for data acquisition, processing, retrieval, and visualization to ensure business continuity.
Scientific Support & Training: Provide expert advice to scientists on application use. Develop comprehensive documentation and deliver training to the scientific community on data applications and databases.
Operational Excellence: Coordinate external resources for operational activities, managing costs, quality, and deadlines for key deliverables. Contribute to the implementation and integration of software developments.

Profile:

PhD or Master’s degree in a scientific field (Biology, Biochemistry, Pharmacology, or related disciplines).
At least 3 years of experience in Data Management within a Research environment (Pharmaceutical industry, Biotech, or equivalent).
Proven expertise in the data management of biological substances and pharmacology.
Strong background in "wet lab" benchwork, allowing for a deep understanding of scientific data origins.
Proficiency in SQL; experience with BigQuery and PowerBI is highly valued.
Demonstrated experience in project management.
A true team player with a proactive mindset.
Excellent interpersonal and professional communication skills, with the ability to present complex data concepts to diverse stakeholders.
Strong organizational skills with a rigorous approach to prioritization and quality.
Professional proficiency in English is required.