Senior Product Owner (Data / AI)

Responsibilities

• Own a Data & AI Product Vertical End-to-End
• Act as the founder of your data/AI domain
• Own vision, scope, quality, and outcomes with minimal supervision
• Translate complex data capabilities into real product value
• Data & AI Product Strategy
• 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
• Working with Analytics & AI Teams
• 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

Requirements

• 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

Benefits

Additional Information

About Incard Incard's mission is to build the financial operating system for entrepreneurs. We are focused on creating a system where business banking, financial tools, and application logic are coordinated into a single control layer. Through the app store, entrepreneurs and developers can build industry-specific functionality as their business evolves. Who We're Looking For We're looking for a Senior Product Owner (Data / AI) who operates like a mini-CEO for our intelligence layer. 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.

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