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 Genomics Editing Digital Enablement Scientist, you deliver solutions that enable efficient and accurate data‑driven decisions throughout the gene editing pipeline; You bring expertise in both computational biology and genetics to design large‑scale data systems and analytical pipelines that power our gene editing efforts; As a key partner and enabler of multi‑disciplinary teams responsible for designing, creating and advancing gene‑edited material, you develop analytical tools that utilize and connect diverse data types—including genetic, phenotypic and environmental data—to help scientists make data‑driven decisions that increase the efficiency and impact of the gene editing program.

Within this role, you demonstrate autonomy in building relationships and networks within your current unit and expand networks cross‑functionally, interacting most often with members of the Crop Genome Editing team while also working closely with partner teams; You serve as a consultant to leadership and others within your discipline and for digital enablement strategy through clear and organized communication; As a member of the Biology and Genome Design community, you actively build your own acumen and capabilities while sharing best practices with others.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Genomics Editing Digital Enablement Scientist, are to:

• Develop analytical tools that connect biological and operations data to support more efficient and accurate decisions across the gene editing pipeline;
• Drive and coordinate multi‑functional teams to enable robust data connectivity and interoperability across the editing pipeline;
• Lead cross‑functional projects with IT, Data Engineering, Genome Editing and other partner teams to automate decision making and connect data to accelerate development of gene‑edited products;
• Translate complex biological processes into scalable digital workflows that support decision making, advancement, and prioritization within the gene editing program;
• Serve as a key communicator and thought partner on digital enablement strategy, clearly articulating requirements, trade‑offs and opportunities to scientific and non‑scientific stakeholders;
• Contribute to and help shape the Biology and Genome Design community by sharing best practices, mentoring peers, and continuously improving analytical and data system capabilities.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• PhD in Genomics, Computational Biology, Evolution, Quantitative Genetics or another relevant scientific field with a minimum of 6 years of relevant experience; or MS with 10+ years of experience developing data systems and analytics pipelines that enable product delivery using genetic and computational biology datasets;
• Demonstrated track record of designing and implementing data systems and analytical pipelines that support decision making and product advancement in research or product development settings;
• Experience analyzing large‑scale biological datasets and developing analytical pipelines using Python, R or similar software environments;
• Strong ability to collaborate and lead in cross‑functional, multi‑disciplinary teams, influencing without authority and aligning diverse stakeholders around shared digital solutions;
• Excellent communication skills, with the ability to translate complex biological concepts into clear digital requirements, workflows and tools for both technical and non‑technical audiences.

Preferred Qualifications:

• Strong understanding of the genomic control of physiological and biochemical pathways in plants or animals and demonstrated experience developing data systems and analytical pipelines that leverage i) genome-wide association GWAs data; ii) QTL analysis, iii)  candidate gene analysis, iv) gene expression analysis, v) molecular marker development, vi) pedigree data.

• Experienced in analysis of large biological datasets, and developing analytical pipelines using Python, R or similar software and languages.

• Demonstrated ability to develop data systems and analytical pipelines that can support a large variation of use cases.

• Demonstrated experience working collaboratively in cross-functional and cross-cultural teams to achieve common goals.
• Ability to lead and influence key stakeholders through challenges and opportunities; facilitates solutions.
• Strong collaboration ability demonstrated through building cross-functional partnerships and influencing others to drive results and solve business problems.