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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Product Owner (Data / AI) - **Company:** Incard - **Location:** UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Data Validation, Machine Learning, Software Product Management, Raw Data, Recommender Systems, Azure Machine Learning, Backend, Data Analytics, Front End Software Development, Data Pipelines - **Published:** September 25, 2026 - **Apply:** https://startup.jobs/senior-product-owner-data-ai-incard-8301235 ## About the Role We're looking for a Senior Product Owner (Data / AI) who operates like a mini-CEO for our intelligence layer., * 4-7+ years of experience in Data Product, Analytics Product, or Data Science-led product roles * Strong background in data science, analytics, or applied machine learning * Experience turning data and models into real product features * Strong understanding of metrics, experimentation, forecasting, and data pipelines * Ability to write clear, structured specs for data and AI-driven systems * Comfortable working with ambiguity, probabilistic outcomes, and imperfect data * Highly organised, analytical, and outcome-focused * Strong communication skills - able to explain complex concepts simply, * Experience in fintech, payments, or financial analytics * Experience with forecasting, anomaly detection, or recommendation systems * Familiarity with BI tools, experimentation frameworks, or ML platforms * Experience working on AI assistants, copilots, or decision-support tools Mindset We Look For * Mini-CEO mentality - you own intelligence outcomes, not just models * Data-first thinking with strong product judgement * Obsession with clarity, trust, and real-world usefulness * Comfortable making decisions with incomplete or noisy data * Low-ego, highly collaborative partner to engineers and data scientists * Startup DNA - fast iteration, ownership, no bureaucracy ## Description You'll own data-driven product domains such as analytics, forecasting, benchmarking, anomaly detection, recommendations, and AI-powered financial insights. You'll work at the intersection of data science, analytics, AI, and product, partnering closely with Analytics, AI, Backend, and Product teams. This role is ideal for someone with a data science or analytics background who wants to turn models, metrics, and signals into clear, actionable product experiences for business users., * Define product use cases for analytics, forecasting, and AI-driven insights * Partner with data scientists to shape models, assumptions, and outputs * Decide what to build vs what to infer, predict, or automate * Define success metrics focused on accuracy, usefulness, and adoption, * Collaborate closely with Analytics and AI teams on data pipelines, models, and features * Turn raw data, signals, and predictions into user-facing insights and workflows * Ensure explainability, trust, and clarity in AI-powered outputs * Balance precision with usability - perfect models that users don't understand are not success Execution & Delivery * Write clear product requirements, specs, and acceptance criteria for data & AI features * Break down complex initiatives into deliverable milestones * Support engineers and data scientists with fast decisions and prioritisation * Manage iterations after launch based on usage, feedback, and performance Quality, Ethics & Reliability * Own validation of data quality, assumptions, and edge cases * Ensure robustness around missing data, anomalies, and model failure modes * Work closely with compliance and risk teams on AI governance and explainability * Ensure responsible use of AI in regulated financial contexts Cross-Functional Ownership * Collaborate with frontend, mobile, backend, and customer-facing teams * Align data products with business, regulatory, and operational needs * Create clear internal documentation for models, metrics, and decision logic * Support hiring and help shape your future data/AI squad ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Designing the intelligence layer: The future of products beyond interfaces](https://www.wearedevelopers.com/videos/2122-designing-the-intelligence-layer-the-future-of-products-beyond-interfaces) - [The Innovation Formula: Fast Prototyping, Data Analysis, and Real User Insights](https://www.wearedevelopers.com/videos/1421-the-innovation-formula-fast-prototyping-data-analysis-and-real-user-insights) - [Building Products in the era of GenAI](https://www.wearedevelopers.com/videos/827-building-products-in-the-era-of-genai) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)