Breeding Data Scientist

Working collaboratively with team members and cross-functional partners, the role contributes to the development, delivery, and maintenance of reporting and analytics applications that provide trusted, accessible decision support.
This role establishes sustainable, scalable, and governed capabilities that connect R&D and commercial product portfolio information. Building on existing workflows, it enables standardized identity alignment, data exchange, traceability, and reuse across internal source systems. Together, these data and analytical capabilities provide a reliable foundation for portfolio management, seed production planning, pricing optimization, and AI-enabled decision support.
Accountabilities:
Own the end-to-end delivery and continuous improvement of data and analytical products, from problem framing and requirements definition through design, development, validation, deployment, and adoption.
Translate complex scientific and business needs into clear product requirements, fit-for-purpose analytical approaches, prioritized work, and measurable outcomes.
Establish governed, scalable capabilities that connect R&D and commercial product portfolio information, enabling standardized identity alignment, data exchange, traceability, and reuse across internal systems.
Develop and deploy analytical and AI-enabled decision-support capabilities for portfolio management, seed production planning, pricing optimization, and other high-value use cases, supported by appropriate validation, explainability, human oversight, and responsible use practices.
Design and maintain reliable analytical applications, data pipelines, reusable components, dashboards, and workflows using fit-for-purpose engineering standards, quality controls, testing, automation, documentation, and secure data access practices.
Partner with scientific, commercial, product, data, platform, and regional stakeholders to align scope and ownership, manage dependencies and trade-offs, communicate recommendations, and support adoption.
Shape the analytical product roadmap by identifying high-value opportunities, reusable capabilities, technical dependencies, and improvement priorities, while providing technical guidance and strengthening capability across the team.
PLEASE NOTE: Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This includes, but is not limited to, OPT, CPT, and H-1B visa holders.
The role requires technical depth, product delivery experience, domain translation, and collaborative leadership to convert complex data, product, and scientific needs into trusted decision-support capabilities.
Required skills and experience:
Advanced degree, or equivalent experience, in data science, quantitative genetics, plant breeding, statistics, computer science, engineering, bioinformatics, or a related quantitative field; Ph.D. preferred.
Strong working knowledge of applied data science, complex multi-source data integration, data quality, reproducibility, and software development practices using Python, R, SQL, or comparable languages.
Demonstrated ability to work in one or more cloud or managed data platforms, such as AWS, Google Cloud Platform, Microsoft Azure, Snowflake, or comparable environments.
Delivering analytical or data products beyond exploratory analysis or prototype development into adoption, maintenance, and operational use.
Working with complex, multi-source datasets while applying appropriate data quality, validation, lineage, and reproducibility controls.
Translating ambiguous scientific or business questions into structured analytical plans, product requirements, delivery priorities, and measurable outcomes.
Partnering with scientific, commercial, product, data, platform, and regional stakeholders to align scope, manage dependencies, clarify ownership, and support adoption.
Applying breeding, germplasm, pipeline, portfolio, or agricultural research data and decision-process knowledge preferred.
Building production analytical applications, dashboards, APIs, data pipelines, or cloud-enabled workflows preferred.

Employment type
Full-time

Work arrangement
Yes