About the job
At Syngenta, we strive to cultivate a collaborative and trustworthy team in the agricultural sector, delivering premium seeds and innovative crop protection solutions that enhance farmers' achievements. To further this mission, we are looking for a Seeds R&D Pipeline Performance Analyst to join our Global Portfolio Operations Team in Durham, NC. This pivotal role will function as a strategic pipeline analyst for Hub and Trait teams, offering independent insights across R&D to construct a cohesive pipeline narrative that can be utilized by internal stakeholders.
The Seeds R&D Pipeline Performance Analyst is tasked with performing comprehensive performance analysis of the global seeds R&D pipeline. The ideal candidate will possess robust analytical and agronomy expertise, capable of translating complex data into clear executive summaries and persuasive pipeline narratives, thereby supporting the success of breeding programs and fostering data-informed decisions at senior levels while aligning with industry standards and competitive benchmarks.
Key Responsibilities:
- Design and maintain analytical frameworks to evaluate germplasm and trait pipeline performance, including KPIs, metrics, and predictive models.
- Track pipeline velocity, identify bottlenecks, and analyze conversion rates across programs while conducting variance analysis between intended and actual outcomes.
- Collaborate with Digital and breeding program leaders to ensure data integrity, analytical relevance, and integration of industry benchmarks.
- Act as an independent checkpoint for pipeline performance, leading root cause analysis of underperformance and unexpected results.
- Generate executive-level reports and presentations that distill intricate pipeline data into actionable strategic recommendations.
- Evaluate resource utilization efficiency across breeding programs and geographical areas to optimize allocation.
- Facilitate scenario planning and strategic decision-making through data-driven insights and recommendations.
- Work alongside IT and data science teams to develop and improve advanced analytical tools and platforms.

