Senior Genome Editing Target Design Scientist

Bayer•Chesterfield, MO

14h

About The Position

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Senior Genome Editing Target Design Scientist Bayer Crop Science's mission is to sustainably enhance agricultural productivity by seamlessly integrating gene editing and digital technologies, empowering farmers to meet the world's growing food demands while safeguarding the environment; In this role, you drive an impactful gene editing program by identifying gene editing targets and alleles that result in desired phenotypic impact, working with a diverse set of data inputs to develop genotype‑to‑phenotype predictions using some of the industry’s most extensive and global agriculture and genetic datasets; You foster new, game‑changing ideas to produce sophisticated insights that leverage rapidly developing datasets and model‑based approaches to guide genome editing and crop improvement efforts, and you work as an individual contributor within a collaborative team of Data and Trait Scientists; As a member of the Biology and Genome Design community, you actively build your own acumen and capabilities while modeling best practices for others and partnering closely with cross‑functional scientific, engineering, and IT teams across the company.

Requirements

PhD in Biological Sciences, Computational Biology, or a related field
At least 3 years of post‑PhD experience working in gene editing, functional genomics, or closely related fields
Demonstrated ability to collect, analyze, and leverage complex biological datasets and translate them into testable hypotheses
Experience with advanced computational and analytical tools in molecular biology, genetics, and biochemistry
Distinct communication skills with fluency in English, both written and verbal

Nice To Haves

Educational preparation or applied experience in at least one of the following areas: Plant Biology, Genetics, Molecular Biology, Machine/Deep Learning, or other closely related discipline
Demonstrated experience working collaboratively in cross‑functional and cross‑cultural teams to achieve common goals
Ability to influence key stakeholders by articulating challenges and opportunities to drive solutions to complex scientific and organizational challenges
Results‑oriented mindset with demonstrated ability to prioritize and advance multiple projects at the enterprise level.

Responsibilities

Produce and document recommendations for alleles that deliver desired phenotypic impact, contributing to innovative gene editing strategies
Develop and apply state‑of‑the‑art genetic discovery tools to identify novel genetics with predicted optimal phenotypic performance by leveraging diverse genomic and phenotypic datasets
Develop robust workflows and analysis pipelines that enable cross‑team communication, data sharing, and decision‑making, supporting iterative learning from key experiments to shape research direction
Identify and refine methods for capturing complex genetic interactions and the influence of genetic variation on observed phenotypes to improve design and prediction for current and future gene editing pipelines
Lead or assist in the gathering, curation, quality control, and analysis of new data sources (e.g., functional genomics, phenomics) across Research and Development (R&D) teams
Collaborate closely with cross‑functional and cross‑cultural scientific, engineering, and IT partners to align gene editing and data science approaches with pipeline and business needs
Influence key stakeholders by clearly communicating data‑driven insights, challenges, and opportunities to facilitate solutions to complex scientific and technical problems.