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# Genomics Data Scientist - #01RPZ

- **Company:** Monsanto
- **Location:** St. Louis, MO, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Big Data, Computational Biology, Databases, Graph Database, Python (Programming Language), Machine Learning, Population Genetics, High Performance Computing, Modeling and Simulation
- **Published:** November 7, 2026
- **Apply:** https://www.agcareers.com/bayer/genomics-data-scientist--01rpz-job-676762.cfm

## About the Role

* PhD in Quantitative Genetics, Statistics, Evolutionary Biology, Population Genetics, Genomics, Systems Biology, Computational Biology, Applied Mathematics, or related field of study
 * Strong problem solving and critical thinking skills
 * Working knowledge of complex trait genetics
 * Proficiency working with very large data sets and high performance computing
 * Demonstrated fluency with Python and/or R
 * Experience presenting results to varied audiences & influencing project direction/strategy
 * Excellent interpersonal skills and the ability to work effectively in a team-based and cross-functional team environment.

Preferred Qualifications:

 * Experience with cloud based computing on AWS
 * Proficiency in Machine learning algorithms and concepts
 * Experience building relational or graph databases

## Description

Bayer is seeking a highly motivated Genomics Data Scientist to become an integral member of the Global Breeding Genetic Modeling and Simulation team. This role will be responsible for development and implementation of methods that combine statistical modelling and genomic datasets for phenotype-to-genotype analytics to further precision breeding for tomorrowâ??s crops.

You will have access to state of the art analytics platforms, simulation platforms, historical testing data, genomic and phenomic datasets, and a field testing network. Establishing key relationships and networks across Breeding, Biotechnology, and R&D IT is critical. The outcomes of this work should significantly impact the future design of ongoing breeding programs including pipeline architecture, population selection, field testing strategies, and advancement decisions.

Responsibilities:

 * Develop methods and perform analysis that connect genotypes and haplotypes to desired traits in row crop products.
 * Develop strategies to fully leverage genomic insights in breeding decisions.
 * Key contributor to creation of a database of Monsantoâ??s accumulated germplasm knowledge for breeding decisions
 * Key contributor to development, with R&D IT, of internal tools to facilitate both large scale and custom genotype-to-phenotype analytics
 * Key contributor to breeding collaborations on gene editing and genome design