Data Science Manager
Function: Data & AI Solutions
Location: Hybrid, London or Peterborough office
Curious about what’s next?
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we’re a purpose-driven business powered by tech and AI. We’re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We’ve carved a meerkat-shaped niche and we’re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you’ll fit right in.
We’d love you to be part of our journey.
Compare the Market is at an inflection point. We are shifting from a business that answers data questions to one that builds the intelligence powering our AI systems and platform.
As a Data Science Manager in our Data & AI Solutions team, you will lead a team building the models and pipelines that sit at the heart of that platform. Depending on the domain, that might mean understanding in near real-time how hundreds of insurance partners are pricing risk across millions of customer segments, predicting which of our 34 million customers is about to need a better deal, or building the models that power personalisation in our app. These are problems where the answer does not exist in the data yet; your team builds the systems to find it.
You will set technical direction, develop your team, and work closely with product, commercial, and engineering colleagues to ensure the intelligence your team builds has a real effect on the business.
Some of the great things you'll be doing:
Building Intelligence for Our AI Platform
- Lead your team in building predictive systems that run continuously - always-on models that surface signals and feed our AI platform
- Design and oversee automated workflows that take model outputs through to decisions and actions
- Shape how your team approaches AI-powered systems, including where LLMs, retrieval-augmented generation, and multi-step AI patterns add value
- Ensure every model your team ships connects to a real outcome and has a mechanism to improve over time
Technical Leadership
- Set the standard for modelling quality, reproducibility and production-readiness across your team - including model monitoring, drift detection and retraining cycles
- Take ownership of model performance in production: knowing when a system is degrading and having a plan to address it
- Be hands-on in design sessions, code reviews, and architectural decisions where your input matters
- Guide your team through a fast-moving tooling landscape: knowing when a classical model is the right call, when an LLM adds value, and when a more orchestrated approach is needed
- Champion responsible, auditable AI - particularly important in a regulated financial services environment where precision and explainability are non-negotiable
- Encourage and model the use of AI-assisted development tools within your team, and be actively curious about how automated coding and workflow tools can increase the pace and quality of your team's output
Stakeholder Partnership
- Work closely with commercial, product, and engineering leads to translate strategic priorities into well-scoped data science work
- Present model outputs in terms of decisions and outcomes, and contribute a credible data science perspective to planning and prioritisation conversations
Growing Your Team
- Develop your data scientists through regular feedback, technical mentorship, and honest career conversations
- Contribute to hiring, helping bring in people who combine technical rigour with curiosity and commercial awareness
- Contribute to standards and practices across the wider Data & AI Solutions chapter
What we'd like to see from you:
The Essentials
- Experience leading data science teams and delivering ML solutions that run in production
- Strong Python and modelling fundamentals, sufficient to assess your team's work and contribute directly when needed
- A track record of taking models beyond the development environment and connecting them to decisions, workflows, or products with a measurable effect
- Direct experience of model production responsibilities: monitoring, degradation, retraining, and lifecycle management
- Clear communication; able to make technical work legible to commercial and product audiences
- Experience with MLflow, model registries, Databricks, or similar ML lifecycle and platform tooling
Highly Valued
- Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain
- Familiarity with multi-step AI patterns, building systems where models plan, retrieve information, and take sequences of actions
- Understanding of experimentation at scale and the infrastructure needed to run it well
Why Compare the Market?
We’re a business built for pace and performance. Here, you’ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we’re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you’re ready to stretch yourself, raise the bar, and grow with a team that’s serious about performance, innovation, and purpose, we’d love to hear from you.
