Hybrid AI-Ready Research Data Modeling Scientist

DSM-Firmenich AG; Princeton (NJ); Hybrid; USD 100,000 - 140,000; Full time

Job summary

dsm-firmenich seeks a Scientist, Research Data Modeling to design and deliver data models transforming diverse scientific data into trusted, reusable, AI-ready assets. You’ll partner with scientists, data engineers, and governance teams to create practical data structures for research data products across formulation, lab workflows, and omics domains.

The role emphasizes hands-on modeling across conceptual to physical layers, with exposure to modern data platforms and a culture of ongoing

Qualifications

• 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.

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.

Skills

Data modeling

Data analysis

Collaboration

Scientific data literacy

Education

Bachelor’s degree in a scientific field

Master’s degree in data/engineering/informatics

PhD in a related discipline

Tools

Databricks

Delta Lake

dbt

SQL

Python

Cloud data platforms

Job description

dsm-firmenich seeks a Scientist, Research Data Modeling to design and deliver data models transforming diverse scientific data into trusted, reusable, AI-ready assets. You’ll partner with scientists, data engineers, and governance teams to create practical data structures for research data products across formulation, lab workflows, and omics domains.

The role emphasizes hands-on modeling across conceptual to physical layers, with exposure to modern data platforms and a culture of ongoing