Scientist, Research Data Modeling - Princeton, NJ
Listed on 2026-10-10
-
IT/Tech
Data Scientist, Data Analyst, Information & Knowledge Management -
Research/Development
Data Scientist, Information & Knowledge Management
Scientist, Research Data Modeling
Location:
Princeton, NJ
We are seeking a Scientist, Research Data Modeling to join our Data Science & AI organization, working within the Research Data Domain. In this role, you will design and deliver data models that help transform diverse scientific, experimental, and operational research data into trusted, discoverable, reusable, and AI-ready assets.
You will work closely with senior data modelers, scientists, data engineers, data governance specialists, and platform teams to support research data products and use cases across formulation, ingredient discovery, laboratory workflows, experimental data, and other scientific domains.
The ideal candidate has a strong foundation in data modeling, good technical understanding of modern data platforms, and an interest in applying data management and modeling practices to complex research environments.
Key Responsibilities- Design and maintain conceptual, logical, and/or physical data models for research and scientific data domains.
- Work with scientists and business stakeholders to understand data needs, capture requirements, and translate them into practical data structures.
- Collaborate with data engineers and platform teams to implement models in Databricks environments, or other enterprise data platforms.
- Apply data modelling standards and best practices, including FAIR principles, metadata management, semantic clarity, and reusable data design.
- Work in multidisciplinary teams across Science & Research, Data Science & AI, Digital & Technology, and business domains.
- A rich history and a promising future of bold scientific innovation and passionate creation for our customers in health, nutrition, and beauty.
- The opportunity to shape foundational research data capabilities that enable analytics, AI, and scientific innovation.
- A hybrid working environment with competitive benefits and a clear scientific career progression within Science & Research.
- A global, diverse, and multicultural team of colleagues across scientific, technical, and business disciplines.
- A space to grow by encouraging curiosity, openness, experimentation, and continuous learning.
- Barrier-free communities where every employee is equally valued and respected, regardless of background, beliefs, or identity.
- An eagerness to be one team and learn from each other to bring progress to life and create a better future.
- PhD, Master’s, or Bachelor’s degree in a scientific, engineering, data, informatics, or related discipline, with relevant experience in research, data modelling, data analysis, engineering, or informatics.
- Typically 2+ years of relevant experience for Master’s/Bachelor’s candidates;
PhD candidates with relevant research/data experience are also encouraged to apply. - Hands‑on experience in conceptual, logical, and/or physical data modelling, including approaches such as dimensional, Data Vault, semantic, or entity‑relationship modelling.
- Experience or strong interest in research, R&D, laboratory, formulation, nutrition, biotech, pharma, microbiome, omics, or related scientific data environments.
- Working knowledge of FAIR principles, metadata, data quality, data governance, stewardship, reusable data products, and modern data platforms/tools such as Databricks, Delta Lake, dbt, SQL, Python, or cloud data platforms.
- Strong communication and collaboration skills, with the ability to work across scientists, data engineers, governance teams, and technical stakeholders to turn ambiguous requirements into structured data models.
The salary or hourly wage scale provided reflects the pay range dsm-firmenich expects to pay the successful candidate for the position. Individual pay offered will be based on the applicant’s job-related skills,…
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