Product Owner (AI Trade Planning), Digital Venture

Product Owner – Ai Trade Planning

The Product Owner – AI Trade Planning will be responsible for defining and delivering products that automate campaign and assortment planning. The ideal candidate will have a strong foundation in machine learning concepts, data-driven decision-making, and product strategy, coupled with a deep understanding of e-commerce merchandising and campaign workflows.

This role requires a unique blend of business acumen and technical understanding - someone who can work with campaign planners and data scientists to build tools to automate manual campaign setup with intelligent automation.

Key Responsibilities

Product Strategy & Vision

• Define the roadmap for AI/ML-based trade planning and campaign automation tools
• Translate campaign team workflows into scalable, data-driven systems for SKU and collection selection
• Identify and prioritize opportunities for automation and personalization using machine learning

Collaboration & Execution

• Partner with data science, engineering, and campaign teams to design, test, and deploy AI-based solutions for trade planning.
• Work with AI/ML teams to conceptualize models that optimize product inclusion, campaign timing, and personalization.
• Collaborate with marketing, merchandising, and analytics stakeholders to align system outputs with business goals.

Product Design & Delivery

• Define product requirements, user stories, and acceptance criteria for automation tools.
• Oversee prototype development, pilot programs, and scaling of ML-driven trade planning systems.
• Evaluate and iterate on product performance using measurable success metrics (e.g., revenue uplift, manual effort reduction, personalization accuracy).

Data & Insights

• Leverage historical campaign data, user behavior, and product performance to inform model design and prioritization.
• Analyze results and create data-driven business presentations for leadership review.
• Serve as the business liaison for AI/ML initiatives - interpreting model outcomes for non-technical stakeholders.

Change Management

• Drive adoption of AI-led trade planning among campaign teams through clear communication, documentation, and training.
• Work cross-functionally to ensure smooth integration of AI solutions into existing workflows and planning cycles.