Job Specifications
Company Description
Datanoetic is an early-stage UK-based start-up set to disrupt AI driven process automation and data value generation areas for supply chains processes. With deterministic and generative AI capabilities at its core, the Datanoetic platform is built on value-stream mapping (VSM), a proprietary value KPI framework, knowledge graphs and a composable architecture.
Once implemented, the platform starts with helping to visualize and track processes in real-time, after which it learns, helps simulate, and then supports building Agentic AI based autonomous workflows and apps into customer environments.
We help enterprises improve quality, increase efficiency and productivity, cut costs, and make better decisions with AI. We focus especially on complex retail and logistics environments: omni-channel retail networks, distribution centres, fulfilment hubs, cross-dock operations and transportation/3PL operations where every second and every SKU movement matters.
For more, see our website (www.datanoetic.ai)
Role Summary
The Senior Product Owner is responsible for driving the features, functionality and capabilities of the core platform, aligned with our business and value proposition strategy and needs from customers, with a focus on retail and logistics.
This is a critical role part of the senior management, suited for someone who combines:
• Hands-on experience in retail and/or logistics operations and process improvement
• Strong product ownership skills and comfort working with engineering, data and customer teams
• A genuine interest in using data and AI to generate measurable value in supply chains
You will partner closely with the CEO, CTO and the Founder, Chairman to translate real-world operational problems into a clear, prioritised backlog and high-impact product releases.
Key Responsibilities
1. Product Vision Support & Roadmap Input
Contribute to the product vision and strategy for Datanoetic, with a focus on retail and logistics use cases.
Support the product development team in turning market, customer and operations insights into concrete, prioritised roadmap items (epics, features, experiments).
Provide a strong voice on what matters most to users in warehouses, DCs, stores, and transport operations.
2. Backlog Management & Delivery
Own and manage day-to-day product backlog items: write user stories, define acceptance criteria and clarify requirements.
Prioritise backlog based on business value, risk, feasibility and customer impact.
Collaborate with the product development team to plan sprints, refine stories and resolve ambiguities.
Review completed work against acceptance criteria and provide clear feedback to ensure features are usable and valuable.
3. Supply Chain Process & Value Subject Matter Expertise
Act as an SME for retail and logistics processes: inbound, storage, picking, packing, shipping, replenishment, returns, transport planning and execution.
Lead or support value-stream mapping sessions with customers to understand their end-to-end flows and pain points.
Help define value metrics and KPIs (e.g. order cycle time, pick productivity, dock-to-stock time, on-time in-full, cost per order, inventory accuracy, dwell time, etc.) that Datanoetic will track.
Work with customers and internal teams to describe what “value gain” and “value loss” look like at each key step of the process.
4. Customer Discovery & Feedback Loops
Run discovery calls, workshops and interviews with retail and logistics customers to understand their needs and workflows.
Observe how customers use the platform (or similar tools today) and capture insights for product iterations.
Maintain structured feedback loops with early adopters and pilot customers and convert learning into new stories and enhancements.
5. AI-Enabled Feature Design
Collaborate with the product development team to design features that use deterministic and generative AI in practical, explainable ways (e.g. recommendations, alerts, AI copilots for process owners, agentic workflows).
Ensure each proposed AI use case has a clear value hypothesis, input data definition and measurable outcomes.
Help shape how Datanoetic’s “digital brain” represents processes, events and value signals in retail and logistics environments.
6. Go-live Support & Value Realisation
Support implementation during pilots and go-lives: clarify configuration options, workflows, and expected outcomes.
Help define success criteria and value KPIs for each deployment and make sure they are tracked.
Collect and synthesise learnings from implementations and bring them back into the product backlog.
Outcomes & Success in this role will be measured by:
Adoption and depth of usage of core features by retail and logistics customers
Measurable value delivered (e.g. reduced lead times, improved productivity, better service levels, cost and waste reduction)
Quality and clarity of backlog items and requirements
Positive feedback from customers, and intern