Data Scientist - Product Analytics

Product Analytics has embraced AI-native ways of working across our analytical workflows, and we're now moving from adoption to transformation — systematically advancing our analytical assets through an agentic maturity framework we designed ourselves.

The Role

As a Data Scientist you are curious, analytically capable, and excited about learning AI-native ways of working. You'll build upon your foundations in data science, Python, and SQL while learning to combine them with AI tools that are central to how our team operates.

• Apply Data Science methodology: including feature engineering, model development, and testing with attention to quality
• Build AI-native analytical solutions: Move from simple AI assistance through to agentic workflows, contributing to our agentic maturity framework with guidance from senior team members.
• Apply and critically evaluate AI outputs: Use AI tools daily to enhance your workflows and develop the skill of knowing when to trust, refine, or override what AI generates.
• Contribute technically across the data lifecycle: Work across data extraction, cleaning, feature engineering, and model development using cloud platforms such as GCP, Azure, and AWS.
• Design scalable, reusable approaches: Create specifications engineering teams can implement and build analytical solutions that can be applied across different business challenges.
• Collaborate and share knowledge across teams: Work alongside analysts, engineers, and product specialists across geographies — sharing what you learn and contributing to AI-native practices.
• Support delivery and continuous improvement: Contribute to project delivery, help resolve analytical questions, and suggest improvements to our processes, timelines, and methods.

• 1-5 years of experience in data science, AI/ML development, or technical consulting
• Strong Python and SQL programming skills for data analysis and manipulation
• Solid understanding of data science fundamentals: data preparation, modelling approaches, and validation methods
• Familiarity with version control and documentation practices
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP)
• Strong communicator — able to explain complex technical concepts clearly to non-technical audiences
• Experience using AI tools (Claude, ChatGPT, GitHub Copilot, or similar) in your work or studies — or genuine enthusiasm and a clear willingness to learn
• Understanding of ML/AI fundamentals including how LLMs work, transformer architectures, and when to apply different approaches

Remember – you might not tick all the boxes, but don’t let that from stopping you applying. We’re more interested in how you work, your ability to solve problems and think big.

Working at Quantium will allow you to challenge your imagination. You will get to solve complex problems using rigor, precision and by asking great questions – but it also means you can think big, outside the box and push your problem-solving skills to the max.

By joining the Quantium team, you’ll get to:

• Forge your path: So many of our team have moved around different teams or offices. You’ll be in the driver’s seat, and we empower you to make your career your own.
• Find your kind: Embrace diversity and connect with your tribe (think foodies, dog lovers, readers, or runners).
• Make an impact: Leave your mark. Your contributions resonate, regardless of your role or rank.

We’ve got some pretty sweet perks: 

• Flexible work arrangements: Achieve work life balance at your own pace with hybrid and flexible work arrangements.
• Continuous learning: Our vision is empowering analytics talent to thrive. The Analytics Community fosters the development of individuals, thought leadership and technical excellence at Quantium through building strong connections, fostering collaboration, and co-creation of best practice.
• Remote working: Embrace the opportunity to work outside of your assigned home location for up to 30 days every year.