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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Breeding Data Scientist - **Company:** Syngenta - **Location:** Durham, NC, United States (Remote available) - **Salary:** $104,800.0 - $157,200.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Security, Decision Support Systems, Electronic Data Interchange (EDI), R (Programming Language), Python (Programming Language), Software Engineering, Software Requirements Analysis, SQL Databases, Google Cloud, Snowflake, Information Technology, Data Management, Data Pipelines - **Published:** September 28, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d9ddc8efbed5e9ee ## About the Role 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., * 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. ## Description 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., * 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. ## Related Videos - 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