AI Digital Product Manager - Vegetables Supply Chain at Syngenta Group

Durham, Illinois, United States -

Full Time

Start Date

Immediate

Expiry Date

11 May, 26

Salary

0.0

Posted On

10 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Roadmap Ownership, Cross-Functional Translation, Algorithm Lifecycle Management, Value Monitoring, Bias Monitoring, User-Centric Design, Global Scaling, Change Management, AI/ML Advancements, Product Vision, Supply Chain Planning, Production Optimization, Inventory Optimization, Agile Product Management, Team Leadership, Jira/Confluence

Industry

Farming

Description

Company Description At Syngenta Vegetable Seeds, we’re passionate about helping people in the vegetable industry succeed and putting growers at the heart of all that we do. Our energies are focused on creating solutions that help them get more out of their crops, now and in the future. A commitment in every seed. We do this by protecting seed, bulbs, or small plant quality from the start to enable growers to achieve the highest yield potentials in their operations; continually investing in R&D to bring cutting-edge innovations to the market; and striving to make a real-world difference through more sustainable practices on farms, in shipping, and at the grocery store. Job Description 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 IT & Digital Team is seeking a AI Digital Product Manager - Vegetables Supply Chain in Chicago, IL; Durham, NC, or Boise, ID. The Supply Chain AI Product Manager is the visionary and orchestrator for our intelligent supply chain utilizing agentic AI. You will define and lead the roadmap and execution for AI/ML solutions—such as Forecasting, Demand Confirmation, Production Planning and Inventory Optimization—ensuring these tools solve real-world operational pain points across our Global network. Accountabilities: AI Roadmap Ownership: Identify and prioritize AI use cases within the supply chain (e.g., using AI to predict factory downtime in an MES or optimizing safety stock in EWM). Communicate product vision, strategy, and updates to stakeholders at all levels. Cross-Functional Translation: Translate complex business problems from Supply Chain Leads into business and technical requirements for Software Engineers, Data Engineers and Data Scientists. Algorithm Lifecycle Management: Oversee the "Productization" of models—ensuring they move from a pilot/notebook phase into a global production environment. Value & Bias Monitoring: Define KPIs to measure the accuracy of AI forecasts and ensure models remain unbiased and performant across different global regions. User-Centric Design: Work with Business Analysts to ensure AI outputs are presented in a way that is intuitive and actionable for a warehouse manager or a production planner. Global Scaling: Lead the "rollout" strategy for AI products, ensuring that a forecasting model built for Europe is successfully adapted for the nuances of our Asian or African markets. Collaborate with Production & Supply leadership team on change management and adoption of developed AI Tools. Stay current with advancements in AI, ML, and automation specific to the production & supply industry and assess their potential impact on the organization. Actively seek and propose opportunities to leverage AI, ML, and automation technologies to enhance business processes, decision-making, and operational efficiency. Lead a team including a product designer and data scientist and work in close collaboration with the AI Software Engineering Team and Vegetables IT Delivery Lead. Qualifications PLEASE NOTE: Candidates must be legally authorized to work in the United States on a permanent basis without requiring current or future sponsorship (which also includes OPT/CPT and H-1B visas). Bachelors in Supply Chain, Information System, Business Administration, or Computer Science. Minimum 5 years of experience in product management or program ownership. Domain Expertise: Deep understanding of supply chain pillars: Planning, Production, Logistics, and Quality Management. AI/ML Literacy: Strong conceptual understanding of Machine Learning (Regression, Time-Series, Neural Networks) and the Data Lifecycle (Ingestion, Cleaning, Modeling). Technical Stack: Familiarity with AI tools (e.g., Azure AI, AWS Agent Core, Databricks or Google Vertex AI) and how they integrate with ERP (SAP). AI Orchestation & Framework knowledge. Agile Product Management: Experience using Jira/Confluence to manage a product backlog and lead sprint ceremonies. Additional Information What We Offer: A culture that celebrates diversity & inclusion, promotes professional development, and strives for a work-life balance that supports the team members. Offers flexible work options to support your work and personal needs. Full Benefit Package (Medical, Dental & Vision) that starts your first day. 401k plan with company match, Profit Sharing & Retirement Savings Contribution. Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits. Syngenta has been ranked as a top employer by Science Journal. Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. WL: 5B #LI-Hybrid

Responsibilities

The role involves defining and leading the roadmap and execution for AI/ML solutions within the supply chain, such as forecasting and optimization, to solve real-world operational pain points globally. Key accountabilities include translating business problems into technical requirements, overseeing model productization, monitoring performance, and leading the rollout strategy for AI products across different global markets.