Sr Genome Editing Operations Scienti

Bayer•Chesterfield, MO

About The Position

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; As a Genome Editing Operations Scientist, you guide the development of an increasingly efficient gene editing pipeline by building connected data systems that drive decisions; You connect disparate data sources and leverage key advancement data to group projects, reagents, and samples, using this connected data system to deliver models that optimize resource use and pipeline capacity by integrating data awareness across lab, greenhouse, and field operations; In this role, you clearly communicate plans, progress, and responsibilities to stakeholders and balance early delivery and release with best practices, FAIR data principles, and transparency within the Biology and Genome Design community and the broader Crop Genome Editing team. The primary responsibilities of this role, Genome Editing Operations Scientist, are to: Guide the development of highly connected data systems that enable data‑driven, model‑based analytics to improve pipeline effectiveness and efficiency; Work with multifunctional teams to enable data connectivity across the editing pipeline, integrating information from lab, greenhouse, and field operations; Collaborate with partner teams across Crop Science (Gene Editing, IT Enterprise, Data and Engineering) to automate decision making and improve operational efficiency to accelerate development of gene‑edited products; Serve as a key communicator translating business data knowledge and operational workflows into clear technical implementation plans for data scientists, data engineers, and developers; Demonstrate autonomy in building relationships and networks within your unit and across functions, most often with members of the Crop Genome Editing team and closely aligned partner teams; Act as a consultant to leadership and colleagues on digital strategy and data‑driven operations through clear, organized, and influential communication; Actively build your own acumen in biology, genome design, and digital operations while sharing best practices and learnings with the broader Biology and Genome Design community.

Requirements

PhD in Computational Biology, Computer Science and Engineering, or another relevant scientific field with a minimum of 6 years of relevant experience, or MS with 10+ years of relevant experience
Demonstrated track record developing data systems and pipelines that enable efficient product delivery and operational modeling
Demonstrated experience working collaboratively in cross‑functional and cross‑cultural teams to achieve common goals
Demonstrated experience leading and influencing activities of cross‑functional teams without direct reporting relationships
Ability to lead and influence key stakeholders through challenges and opportunities and to facilitate solutions

Nice To Haves

Experience building data pipelines as a ML DevOps Engineer or Data Engineer (or equivalent) with strong proficiency in open‑source tools, containerization, and orchestration tools, as well as experience with data versioning and model management tools
Experience with Operations Research in industries with time‑sensitive delivery and a laboratory component
Experience analyzing large biological datasets and developing analytical pipelines using Python, R, or similar software and languages, including experience with cloud development environments (for example, Google BigQuery, AWS, or similar)
Experience working in cross‑functional settings spanning gene editing, IT, data science, and engineering in an R&D or product development environment

Responsibilities

Guide the development of highly connected data systems that enable data‑driven, model‑based analytics to improve pipeline effectiveness and efficiency
Work with multifunctional teams to enable data connectivity across the editing pipeline, integrating information from lab, greenhouse, and field operations
Collaborate with partner teams across Crop Science (Gene Editing, IT Enterprise, Data and Engineering) to automate decision making and improve operational efficiency to accelerate development of gene‑edited products
Serve as a key communicator translating business data knowledge and operational workflows into clear technical implementation plans for data scientists, data engineers, and developers
Demonstrate autonomy in building relationships and networks within your unit and across functions, most often with members of the Crop Genome Editing team and closely aligned partner teams
Act as a consultant to leadership and colleagues on digital strategy and data‑driven operations through clear, organized, and influential communication
Actively build your own acumen in biology, genome design, and digital operations while sharing best practices and learnings with the broader Biology and Genome Design community