At a Glance
- Tasks: Dive into data, design experiments, and enhance transaction data with AI tools.
- Company: Join a forward-thinking AI team in a dynamic tech environment.
- Benefits: Competitive salary, flexible working hours, and opportunities for personal growth.
- Other info: Collaborative culture with a focus on continuous learning and career advancement.
- Why this job: Make a real impact by solving complex problems and innovating with AI.
- Qualifications: Strong SQL skills, Python experience, and a passion for data analysis.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- You're naturally curious. When you see messy or imperfect data, you want to understand why.
- You’re also curious about modern AI and LLM tools and have experimented with using building things with them, at work or as personal projects.
- Comfortable being given a broad problem and figuring out how to structure it.
- You enjoy forming hypotheses, writing code to test them, and interrogating results deeply.
- Strong SQL skills and ideally experience using Python for exploratory analysis or prototyping.
- You’ve worked in a data-led, fast-paced environment (e.g. fintech, banking, start-up, consulting).
- Ability to communicate clearly and can explain complex findings to both technical and non-technical audiences.
- You’re collaborative but independent — you don’t wait to be told the next step.
What the job involves
- We’re looking for a Senior Product Analyst to join our AI tribe. This is a builder-style role focused on improving how transaction data is enriched, structured and trusted - and on raising the bar for how we experiment and learn.
- This role is about owning ambiguous problems, designing thoughtful experiments, and pushing systems forward through curiosity and disciplined analysis of the outcomes.
- Explore the current enrichment pipeline to understand how it works and where it fails.
- Form hypotheses about where accuracy is breaking down (e.g. merchant ambiguity, edge cases, new patterns).
- Write code (typically SQL and/or Python) to analyse performance, quantify what's working, and identify systematic gaps.
- Build quick prototypes or enrichment experiments to test alternative approaches.
- Run structured evaluations, interpret results carefully, and communicate trade-offs clearly.
- Work closely with Product and Engineering to embed improvements into long-term system design.
- Use AI and LLM tools pragmatically - for exploration, pattern detection, prototyping logic and accelerating experimentation.
- Continuously look for deeper patterns and structural improvements rather than settling for surface-level fixes.
Senior Product Analyst (Artificial Intelligence) in London employer: Zopa
As a Senior Product Analyst in our dynamic AI tribe, you'll thrive in a culture that champions curiosity and innovation. We offer a collaborative environment where your analytical skills will directly impact the enhancement of transaction data systems, alongside opportunities for professional growth through hands-on experimentation with cutting-edge AI tools. Located in a vibrant tech hub, we provide a supportive atmosphere that values independent thinking and fosters continuous learning, making us an exceptional employer for those seeking meaningful and rewarding work.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Analyst (Artificial Intelligence) in London
✨Tip Number 1
Get your hands dirty with the tools! Dive into SQL and Python projects that showcase your skills. Build something cool using AI or LLM tools, and don’t forget to share it on your portfolio or LinkedIn!
✨Tip Number 2
Networking is key! Reach out to professionals in the fintech or AI space. Join relevant online communities or attend meetups to connect with like-minded folks who can help you land that Senior Product Analyst role.
✨Tip Number 3
Prepare for interviews by practising how to explain complex data findings in simple terms. Use examples from your past experiences where you’ve tackled ambiguous problems and turned them into structured solutions.
✨Tip Number 4
Apply through our website! We love seeing candidates who are proactive. Tailor your application to highlight your curiosity and problem-solving skills, and show us how you can contribute to our AI tribe.
We think you need these skills to ace Senior Product Analyst (Artificial Intelligence) in London
Some tips for your application 🫡
Show Your Curiosity:Let your natural curiosity shine through in your application. When discussing your experiences, highlight how you've tackled messy data and what you learned from it. We love candidates who are eager to explore and understand the 'why' behind the numbers!
Demonstrate Your Skills:Make sure to showcase your SQL and Python skills clearly. Include specific examples of projects where you've used these tools for exploratory analysis or prototyping. We want to see how you've applied your technical know-how in real-world scenarios!
Communicate Clearly:Remember, we need someone who can explain complex findings to both technical and non-technical audiences. In your application, try to convey your ability to simplify intricate concepts. This will show us that you can bridge the gap between data and decision-making.
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 culture and values while you're at it!
How to prepare for a job interview at Zopa
✨Show Your Curiosity
Make sure to express your natural curiosity during the interview. Share examples of how you've tackled messy data in the past and what you learned from those experiences. This will demonstrate your eagerness to understand complex problems and your proactive approach to finding solutions.
✨Demonstrate Your Technical Skills
Be prepared to discuss your SQL and Python skills in detail. Bring along examples of code you've written for exploratory analysis or prototyping. If possible, showcase a project where you used these skills to solve a real-world problem, as this will highlight your hands-on experience.
✨Communicate Clearly
Practice explaining complex findings in simple terms. You might be asked to present your analysis to both technical and non-technical audiences, so being able to break down your insights will be crucial. Think of ways to illustrate your points with relatable examples or visuals.
✨Emphasise Collaboration and Independence
Share instances where you've successfully collaborated with teams while also taking initiative on your own. Highlight how you balance working independently with seeking input from others, as this role requires both collaboration and self-direction to tackle ambiguous problems effectively.
