Senior Scientist, Real World Data - Health Insights

dsm-firmenich; Princeton (NJ); Hybrid; USD 140,000 - 170,000; Full time

Benefits offered by this job

Hybrid workplace

Global team environment

Career growth opportunities

Diverse, collaborative projects

Job summary

dsm-firmenich is seeking a Senior Scientist in Real World Data to advance nutrition and health research. The role combines epidemiology, real-world human data, and multi-omics analytics to generate insights for biomarker discovery and evidence generation.

Location options include Princeton, NJ or Columbia, MD with a hybrid work arrangement. You will analyze large-scale cohorts, biobanks, and observational datasets, collaborate across scientific teams, and contribute to publications and external

Qualifications

• PhD required in a quantitative life sciences field.
• 5+ years of post-doctoral experience with human health or population-scale datasets.
• Proven ability to derive actionable insights from complex data.
• Strong programming in Python and R; experience with real-world datasets.

Responsibilities

• Analyze real-world human datasets including cohorts, biobanks, and observational data.
• Evaluate relationships between nutrition, biomarkers and health outcomes for discovery.
• Contribute to publications, talks, and collaborations.
• Collaborate with data scientists, nutrition scientists, microbiome researchers and innovation teams.
• Communicate findings to technical and non-technical stakeholders.
• Engage with academia, consortia and industry partners and stay updated on new datasets and methods.

Skills

Python

R

Multi-omics

Epidemiology

Education

PhD in Computational Biology, Bioinformatics, Epidemiology, Systems Biology, Nutrition Science or related discipline

Job description

dsm-firmenich is seeking a Senior Scientist in Real World Data to advance nutrition and health research. The role combines epidemiology, real-world human data, and multi-omics analytics to generate insights for biomarker discovery and evidence generation.

Location options include Princeton, NJ or Columbia, MD with a hybrid work arrangement. You will analyze large-scale cohorts, biobanks, and observational datasets, collaborate across scientific teams, and contribute to publications and external