Senior Data Scientist, Multiomics & Population Cohorts

University Of Michigan; Ann Arbor (MI); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Excellent medical, dental and vision

2:1 retirement match

Job summary

Senior Data Scientist - Multiomics and Population Cohorts at University of Michigan leads development of proteomics and multi-omics analysis pipelines, deploying AI model inferences at scale across large biobank datasets.

You will construct computational frameworks and cross-cohort data systems, collaborate with postdocs, and contribute to manuscripts and grants while focusing on causal and genetic inference to reveal disease mechanisms in cardiometabolic conditions.

Qualifications

• Masters or doctoral degree in bioinformatics, computational biology, biostatistics, systems biology, or a closely related field.
• Demonstrated experience analyzing large-scale proteomic datasets from high-throughput platforms (Olink or SomaScan).
• Proficiency in R and/or Python for statistical analysis and pipeline development.
• Experience with multi-omic data integration combining at least two of: proteomics, metabolomics, genomics, transcriptomics.
• Familiarity with statistical methods for high-dimensional biological data (dimensionality reduction, regularized regression, survival analysis).
• Strong organizational skills and attention to detail.
• Ability to prepare and present written and code-based (Python or R) analytical reports.
• Strong scientific writing skills; ability to contribute to manuscripts and grant applications.

Responsibilities

• Build, implement, and maintain proteomics and multi-omic analysis pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies
• Deploy AI models to biobank datasets
• Build and maintain cross-cohort data harmonization and proteomic cross-walk tools across derivation and validation datasets
• Perform causal and genetic inference analyses (including Mendelian randomization and mediation analysis) to identify disease mechanisms
• Evaluate pipeline and signature performance; prepare written and code-based analytical reports (Python or R)
• Contribute to manuscripts, grant applications, and presentations
• Coordinate data sharing and computational workflows with collaborative network partners and other research partners
• Other duties as assigned

Skills

R

Python

Multiomics integration

Causal inference

Data harmonization

Education

Masters or PhD in bioinformatics/computational biology/biostatistics/systems biology

Tools

Snakemake

Nextflow

SQL

PostgreSQL

Job description

Senior Data Scientist - Multiomics and Population Cohorts at University of Michigan leads development of proteomics and multi-omics analysis pipelines, deploying AI model inferences at scale across large biobank datasets.

You will construct computational frameworks and cross-cohort data systems, collaborate with postdocs, and contribute to manuscripts and grants while focusing on causal and genetic inference to reveal disease mechanisms in cardiometabolic conditions.