Live opening · Posted 5 days ago

R&D Portfolio Intelligence & Analytics Lead

Syngenta · Durham, North Carolina, United States
Smartrecruiters Hybrid Full-time
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanySyngenta
LocationDurham, North Carolina, United States
Job typeFull-time
Work modeHybrid
SourceSmartrecruiters
Listed5 days ago

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About the role

Description supplied by the original job listing.

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 Shiny to 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 applications or 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.

Employment type
Full-time

Work arrangement
Hybrid

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