Senior Greenhouse & Controlled Environment Operations Analyst

At Syngenta Seeds Field Crops, we're shaping the future of agriculture and empowering farmers to meet the ever-growing demand for food and fuel. We’re a global Ag Tech powerhouse, headquartered in the United States, with passionate, local experts collaborating with farmers to deliver solutions that create market opportunities. We unite precision breeding, advanced biotechnology trait choice, and digital platforms for unmatched in-field performance. Our seeds help mitigate risks such as disease, insect, weed, and extreme weather pressures, all while promoting sustainable farming practices The Senior Greenhouse & Controlled Environment Operations Analyst combines practical experience in agricultural greenhouse and controlled-environment operations with strong analytical capabilities to improve crop pipeline performance, capacity utilization, traceability, and delivery. Based at the Trait Conversion Accelerator (TCA) in Nampa, Idaho, the role supports Trait Introgression (TI) and Double Haploid (DH) pipelines. Direct experience working in or supporting agricultural plant-growing operations in greenhouses, growth chambers, or other controlled environments is required; general data analytics experience alone does not meet this requirement. Working closely with greenhouse, laboratory, and pipeline teams, the role translates operational, environmental, phenotypic, genotypic, and inventory data into practical decisions. It applies knowledge of crop development and plant-growing workflows to capacity planning, planting schedules, workload and budget management, resource allocation, and continuous improvement. The role also governs data architecture, integrates data sources, and develops reliable reporting and decision-support tools that connect biological performance with operational execution. Accountabilities: - Greenhouse and crop pipeline data management: Design, develop, and maintain data architecture, trusted datasets, dashboards, and recurring reports for DH and TI pipelines. Integrate operational, environmental, phenotypic, genotypic, and inventory data from project initiation through planting, controlled-environment execution, selection, advancement, and hand-off. Validate data definitions and outputs with the teams responsible for crop execution. - Crop pipeline performance management: Define, monitor, and report operational and business KPIs for DH and TI execution. Compare crop progression, cycle duration, productivity, and delivery against plans, targets, and internal thresholds. Interpret deviations in their biological and operational context and work with teams to identify improvement priorities. - Greenhouse capacity and workload planning: Analyze greenhouse footprint, space allocation, occupancy, labor demand and availability, planting schedules, crop-cycle duration, environmental conditions, and seasonal constraints. Apply knowledge of crop development and plant-growing workflows to identify bottlenecks and delivery risks, including external dependencies such as genotyping. Develop scenario models and what-if simulations to support project prioritization, resource allocation, budget management, and productive use of available capacity. - Data quality and crop traceability: Establish data-quality standards, cross-checks, and automated controls that prevent, detect, and correct errors in data collection, recording, integration, and analysis. Work with greenhouse and laboratory teams to resolve discrepancies and maintain consistent records and end-to-end traceability across crop and digital workflows. - Controlled-environment and laboratory improvement: Analyze environmental, crop, and laboratory data to investigate performance variation and support structured root-cause analysis. Partner with operational teams to understand how growing conditions and process execution affect crop development, cycle duration, and pipeline outcomes. Use findings to establish realistic productivity targets, prioritize improvements, and measure their impact. - Operational decision support and predictive analytics: Translate complex analytical outputs into concise recommendations for greenhouse, laboratory, and pipeline stakeholders. Apply predictive modeling and AI tools where appropriate to identify patterns, evaluate scenarios, and anticipate operational risks. Ground recommendations in biological and operational constraints to improve footprint utilization, project execution, resource allocation, and digital safeguards that reduce product vulnerabilities. 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. - M.S. or Ph.D. in Agricultural Engineering, Plant Science, Horticulture, Agronomy, Data Science, Data Engineering, Statistics, Industrial Engineering, or a related field. Candidates from agricultural disciplines must demonstrate strong quantitative and analytical training; candidates from analytical disciplines must also meet the required agricultural greenhouse or controlled-environment experience. - Required: Demonstrated experience working in or directly supporting agricultural greenhouses, growth chambers, or other controlled-environment crop production or research facilities. - Proficiency in programming, data analysis, statistics, and performance metrics, with the ability to connect analytical methods to crop and controlled-environment operations. - Strong analytical and problem-solving capabilities, including the ability to distinguish data-quality issues from biological or operational causes of performance variation. - A practical continuous-improvement mindset, with the ability to identify feasible changes that account for crop needs, greenhouse constraints, and available resources. - Excellent written and oral communication skills and the ability to collaborate with greenhouse, laboratory, pipeline, and technical teams in an on-site agricultural research environment. - Ability to translate complex analytical outputs into concise, action-oriented recommendations that clearly explain the operational implications, trade-offs, and expected outcomes. What We Offer: - A culture that celebrates belonging & collaboration, promotes professional development, and strives for a work-life balance that supports the team members. Offers flexible work options to support your work and personal needs.  - Full Benefit Package (Medical, Dental & Vision) that starts your first day.   - 401k plan with company match, Profit Sharing & Retirement Savings Contribution.  - Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits.  Syngenta has been ranked as a top employer by Science Journal.  Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI  Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.    Use of AI in Our Recruitment Process At Syngenta, we use artificial intelligence (AI) to screen applications for high-volume roles. When you submit an application, AI technology assesses your profile against the job requirements and generates a matching score. This score reflects how closely your qualifications, skills, and experience align with the role's criteria as defined in the job description. WL4B #LI-Onsite