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For Companies At a Glance
- Tasks: Lead data-driven product development in AI and analytics for entrepreneurs.
- Company: Join Incard, a pioneering fintech company revolutionising business banking.
- Benefits: Enjoy competitive pay, stock options, generous leave, and global health insurance.
- Why this job: Be a mini-CEO, shaping impactful AI products that empower businesses.
- Qualifications: 4-7+ years in data product roles with strong analytical skills.
- Other info: Dynamic startup culture focused on innovation and collaboration.
The predicted salary is between 48000 - 84000 £ per year.
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.
What You’ll Do
- 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
What We’re Looking For
- 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
Nice to Have
- 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
- 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
Senior Product Owner (Data / AI) employer: Incard
Contact Detail:
Incard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Product Owner (Data / AI)
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to data and AI. We recommend using the STAR method to structure your answers – it helps you showcase your experience clearly.
✨Tip Number 3
Showcase your passion for data and AI during interviews. Share examples of how you've turned complex data into actionable insights, just like you'd do in the role of a Senior Product Owner.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Product Owner (Data / AI)
Some tips for your application 🫡
Show Your Passion for Data & AI: When you're writing your application, let your enthusiasm for data and AI shine through! We want to see how you connect with our mission and how your experience aligns with the role. Share specific examples of projects or products you've worked on that demonstrate your skills in this area.
Be Clear and Concise: We appreciate clarity, so make sure your application is easy to read and straight to the point. Use bullet points where possible to highlight your achievements and skills. Remember, we’re looking for someone who can translate complex ideas into simple, actionable insights!
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Senior Product Owner role. Highlight your relevant experience in data science, analytics, and product ownership to show us why you’re the perfect fit.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company and culture while you’re at it!
How to prepare for a job interview at Incard
✨Know Your Data Inside Out
As a Senior Product Owner, you'll need to demonstrate a solid understanding of data science and analytics. Brush up on key concepts like forecasting, anomaly detection, and AI-driven insights. Be ready to discuss how you've turned complex data into actionable product features in your previous roles.
✨Showcase Your Mini-CEO Mindset
This role requires a mini-CEO mentality, so come prepared to talk about how you take ownership of product outcomes. Share examples of how you've led projects from vision to execution, ensuring that the end product delivers real value to users while balancing precision and usability.
✨Collaborate Like a Pro
Collaboration is key in this position. Be ready to discuss how you've worked with cross-functional teams, including data scientists and engineers. Highlight specific instances where your collaboration led to successful product launches or improvements, and emphasise your ability to communicate complex concepts simply.
✨Prepare for Ambiguity
In the world of data and AI, things can get a bit murky. Show that you're comfortable making decisions with incomplete data and can navigate uncertainty. Bring examples of how you've handled ambiguity in past projects and how you ensured robust outcomes despite the challenges.