D-commerce AI Product Owner

AI Thought Leadership:

• Shape overall plan on AI role within D-comm products
• Bring though leadership on AI insights, execution and agentic builds
• External scanning of best-in-class tools and relevance to Unilever (Build vs. Buy)

Product Vision Strategy:

• Develop and articulate a clear product vision and long-term strategy for our D-commerce AI products, aligned with overall business objectives and market trends.
• Conduct market research, competitive analysis, and customer journey mapping to identify new opportunities and user pain points.
• Define and track Key Performance Indicators (KPIs) and success metrics to measure product performance and inform strategic decisions.

Backlog Management Prioritization:

• Own, maintain, and prioritize the product backlog based on business value, technical feasibility, and customer impact.
• Translate product strategy into detailed user stories, acceptance criteria, and technical requirements for the development team.
• Collaborate with stakeholders across marketing, sales, operations, and customer service to gather requirements and ensure alignment.

MLOps Development Execution:

• Lead cross-functional steering committees to ensure alignment and secure buy-in for major product initiatives.
• Serve as the primary point of contact for the Agile/Scrum development team, participating in all ceremonies (sprint planning, daily stand-ups, sprint reviews, and retrospectives)
• Work closely with UX/UI designers to create intuitive and engaging user interfaces
• Ensure the development team has a clear understanding of the product requirements and priorities, clarifying questions and removing roadblocks
• Accept completed user stories, verifying that they meet the defined acceptance criteria and quality standards.

Executive Stakeholder Management Influence:

• Build and maintain strong relationships with senior leadership and key stakeholders across the organization, acting as a trusted advisor on all things D-commerce.
• Masterfully communicate the product vision, strategy, and progress, tailoring the message to various audiences from the development team to the executive suite.

• AI/ML Fluency: Strong foundational understanding of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI concepts, architectures, and applications in a business context.
• Technical expertise: Data Bricks, Azure or equivalent cloud technologies
• Proficiency in Python, PySpark, Spark streaming, SQL database, DAX, PBI (other relevant BI tool)
• Product: Proven ability to develop and articulate a clear product vision and long-term strategy for AI products, aligned with overall business objectives
• Data MLOps: Familiarity with the data lifecycle, MLOps (Machine Learning Operations) principles, and how to work with data scientists/engineers to define requirements for model development and deployment .
• Technical Acumen: Ability to translate complex business needs into actionable user stories, acceptance criteria, and technical requirements for a development team. e-commerce
• Domain Knowledge: Deep understanding of the Digital Commerce (D-comm) ecosystem, including Retailer/CBD, Retail Media, Content, fulfilment etc

• CD Business domain leader
• Retailer teams
• XOPS delivery teams
• BG and BU D-comm leads
• DT leaders across domains (Consumer, Customer etc)