Senior Director, Scientific Data Strategy & Governance - Princeton, NJ or Lexington, MA

Senior Director, Scientific Data Strategy & Governance

Location: Princeton, NJ or Lexington, MA

 

Looking for a new challenge?  Yearning to be part of an organization that brings progress to life?  Read on! 

 

We’re looking to build our enthusiastic and committed Data Science team.  We’re #hiring for Senior Director, Scientific Data Strategy & Governance.  This global leadership role leads a multidisciplinary team and is accountable for defining, operationalizing, and scaling a data strategy that enables advanced analytics, AI, and scientific discovery across Science and Research. You will own the end-to-end scientific data operating model – spanning data governance, data strategy, data modeling and data operations, data privacy, and data sharing – to ensure scientific data are trusted, compliant, interoperable, AI-ready, and fit-for-purpose across discovery, development, production, clinical, real-world, experimental, and formulation contexts.  You serve as a strategic bridge between Business Units, Science & Research, and Digital & Technology – translating scientific needs into scalable data capabilities that accelerate innovation.

 

Sound intriguing?  There’s more.  You’ll manage a large team of data governance, clinical/RWD real world data) modeling, research data modeling and data strategy & privacy professionals. 

 

At dsm-firmenich, being a force for good is not optional. Diversity, Equity & Inclusion is a shared responsibility woven into our daily work, benefiting our People, Customers & Communities and driving business value. Equal access to opportunities is a given, belonging is a shared feeling, authenticity is celebrated.

 

Your key responsibilities

• Lead a team to define and deliver curated, reusable, AI-ready scientific data products addressing business and innovation needs that directly enable discovery, modeling, and decision-making across ingredients, formulation, clinical/RWD and production process workflows.
• Establish and operate scientific data governance framework covering data ownership, quality, metadata, lineage, access, and lifecycle management to ensure trusted and compliant scientific data across domains
• Own conceptual, logical, and physical data models for key scientific domains; define and maintain canonical data standards, ontologies, and semantic data models that enable interoperability, multi-modal analytics, and consistent AI consumption across science and research.
• Define and execute scientific data strategy spanning internal data domains and external data scouting/acquisition, while embedding privacy-by-design, security, and responsible data use across all scientific data assets.
• Partner with legal, compliance, security and privacy team to operationalize privacy-by-design; establish de-identification, anonymization, and consent-aware usage patterns; enable compliant secondary use of data for research, modeling, and AI.
• Foster relationships and actively collaborate with partnering multidisciplinary Science & Research, Business Innovation teams, and Digital & Tech teams to drive value creation and impact.

 

 

We bring:

• The opportunity to leverage industry-leading expertise across a wide range of scientific disciplines to advance the field and deliver tangible consumer benefits.
• A rich history and a promising future of bold scientific innovation and passionate creation with our customers
• A space to grow by encouraging and supporting curiosity and an open mindset.
• The opportunity to work for a company where sustainability is much more than a claim and is core to our strategy and purpose
• A culture that prioritizes safety and well-being, both physically and mentally
• A firm belief that working together with our customers is the key to achieving great things

 

You bring:

• Minimum 15 years of relevant post-graduate work experience along with minimum 10 years of relevant experience in the life sciences industry required
• Extensive track record of people development and large team (8+ team members) leadership, preferably with global teams, required
• Proven track record defining and operationalizing data strategies, data architecture, or scientific data platform leadership.  Track record managing cross-functional teams that span various projects, multiple locations, and external collabor