Digital Product Advancement and Placement Lead

Syngenta Group•Remote, USA

12d•$106,400 - $152,000•Remote

About The Position

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. To support this mission, Syngenta’s Analytics & Data Sciences Team is seeking a Product Advancement and Placement Lead. This role will use visionary leadership to set the direction for building an integrated, automated, and digitized product advancement and placement workflow, which leverages cutting-edge data science capabilities for customer-centric product development. You will do this by directing a group of team leads that design and maintain solution roadmaps, prioritize capability development across multiple digital product platforms to continuously generate new value. Your group will deliver value through the development and deployment of novel decision science capabilities in global, enterprise tools. The role is accountable for translating scientific and analytical capabilities into deployable decision science solutions that drive measurable business outcomes globally. The role requires a unique blend of technical expertise, knowledge of modern breeding techniques, strong data science and digital fluency, and proven leadership in product and program delivery. Come be a part of the most trusted and compelling company in the industry!

Requirements

Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This comprises, but is not limited to, OPT, CPT, and H-1B visa holders.
Ph.D. or equivalent in Plant Breeding, Plant Science, Genetics, or a related field, with 8+ years of relevant industry experience.
Extensive knowledge of plant breeding and product development pipelines, comprising advancement decision points, stage-gate processes, and multi-environment product evaluation.
Proven experience applying quantitative genetics, statistics, machine learning, and decision science in R&D environments—with demonstrated impact on pipeline decisions and measurable business outcomes.
Experience leading the end-to-end modeling process from problem formulation through development, validation, deployment, and continuous improvement in operational environments.
Track record of building and leading high-performing, multidisciplinary teams spanning science, data science, and engineering in a global matrix organization.
Experience with digital product development principles—including roadmap ownership, backlog prioritization, agile delivery, and user-centric design.
Strong ability to translate complex analytical concepts into actionable insights for both technical and non-technical stakeholders, with excellent communication, influencing, and stakeholder management skills.
Experience partnering with IT organizations to design, develop, and support enterprise software applications at scale.

Responsibilities

Define and lead the strategic direction of the product advancement and placement program by setting priorities for capabilities, ensuring alignment to business objectives and measurable outcomes.
Develop and maintain a comprehensive product advancement and placement.
Translate scientific and business needs into a clear, outcome-driven vision with measurable success metrics for digital workflows and platforms.
Orchestrate the delivery of strategic outcomes across multiple solution teams to deliver differentiated decision science capabilities and measurable business impact.
Navigate a complex, global stakeholder environment by driving alignment where possible and making clear, data-driven prioritization decisions when required.
Develop and sustain a highly engaged, multidisciplinary team of quantitative geneticists, data scientists, data engineers, analytics leads, and product owners, fostering the growth of technical, product, and leadership capabilities.
Build and maintain strong partnerships with R&D IT, Applied Data Science teams, Regional Crop teams, and external collaborators to translate data science, plant breeding, and digital technologies into business value through enhanced analytics and decision-making.
Partner with technical leadership to ensure alignment between business priorities, technical delivery, and scalable implementation.
Contribute to the definition and execution of enterprise analytics strategy, ensuring alignment of product advancement and placement decision science capabilities with business priorities.
Promote a safe work environment and a strong safety culture.