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.
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.
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
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
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
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
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
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
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
Competitive cash-based compensation
Incard stock options
25 days of paid time off per year, plus bank holidays and your birthday off
Global health insurance and unlimited paid sick leave
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