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.
