R&D Portfolio Intelligence & Analytics Lead

R&D Portfolio Intelligence & Analytics Lead

• Full-time

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

At Syngenta, we are advancing agricultural innovation through data-driven portfolio decisions. We are seeking a Portfolio Intelligence & Analytics Lead to strengthen the insights, analytics, and decision-support capabilities that guide our Seeds R&D portfolio.

This role will serve as the analytical engine behind portfolio decisions-combining portfolio strategy, financial and operational analysis, advanced analytics, and technical solution development. You will work across R&D, Finance, Strategy, Digital, and other partners to turn complex portfolio data into clear, actionable recommendations.

In this role, you will help shape how Seeds R&D prioritizes investments, manages trade-offs, and brings innovation forward-using robust analytics and well-designed technical solutions to make portfolio intelligence more timely, transparent, and actionable.

Accountabilities:

• Lead development of portfolio intelligence frameworks, methodologies, and decision-support tools that enable portfolio governance and investment decisions.
• Analyze portfolio value, performance, productivity, scenarios, trade-offs, resource allocation, risks, and investment opportunities.
• Build and enhance analytics, models, dashboards, and reports that help stakeholders understand portfolio performance and make informed decisions.
• Use coding and analytics tools such as Python, R, and Shinyto develop new analyses, automate recurring reporting, and create scalable, interactive solutions.
• Develop predictive analytics, forecasting capabilities, and AI-enabled insights to improve portfolio planning and decision quality.
• Strengthen the portfolio intelligence platform strategy, capability roadmap, and governance processes.
• Ensure high standards for data quality, stewardship, traceability, and consistency across portfolio insights.
• Partner with Finance, Strategy, Digital, and R&D stakeholders to translate business questions into practical analytical products and actionable recommendations.
• Support adoption of portfolio intelligence capabilities through stakeholder engagement, training, documentation, and continuous improvement.

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.

Required Qualifications:

• 5+ years of experience in portfolio analytics, strategy, finance, decision science, business intelligence, or a related field.
• Experience developing executive-level analyses, reports, dashboards, and decision-support materials.
• Strong analytical and problem-solving capabilities, including scenario modelling, resource planning, and data analysis.
• Practical coding experience in Python or R; experience developing
  
  Shiny applicationsor other interactive analytical tools is highly valued.
• Experience building automated reporting, data visualizations, forecasting models, or scalable analytics solutions.
• Knowledge of portfolio-management processes and tools, including project, program, or portfolio management platforms.
• Ability to understand business processes, data structures, governance requirements, and technology platforms-and connect them to meaningful business outcomes.
• Strong communication and stakeholder-management skills, with the ability to explain complex analysis clearly to technical and non-technical audiences.

Preferred Qualifications:

• Advanced degree in Statistics, Agronomy, Data Science, Agricultural Sciences, or a related discipline.
• Experience with agricultural pipeline-management systems, agricultural economics, or commercial analytics.
• Experience with cloud-based analytics platforms, automation tools, and AI/ML-enabled analytical approaches.
• Familiarity with competitive intelligence, market analysis, or the agriculture sector.

What We Offer:

• A culture that celebrates belonging &…