Data Scientist

Data Scientist 

Function: Data 
Location: Hybrid, London 

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.

As a Data Scientist at Compare the Market, you’ll play a key role in developing AI and machine learning solutions that improve customer journeys, pricing intelligence, and product personalisation. Working cross functionally alongside engineers, analysts, and product managers contributing to real-world applications of machine learning that impact millions. ​

Some of the great things you’ll be doing: 

AI Solution Delivery 

• Contribute to the development of machine learning solutions from design through to deployment 
• Build and evaluate predictive models using Python and SQL 
• Translate business challenges into structured data science problems 

Applied Science & Experimentation 

• Conduct statistical analysis and feature engineering to generate actionable insights 
• Support A/B test design, evaluation, and interpretation with rigour and clarity 
• Collaborate with stakeholders to ensure data science solutions are well aligned to product and business needs 

Platform & Practices 

• Work with ML Engineers to support deployment, monitoring, and performance tracking of your models 
• Contribute to team standards on reproducibility, documentation, and model evaluation 
• Apply responsible AI practices to ensure fairness and transparency 

Team & Learning 

• Take part in peer reviews, knowledge sharing, and internal learning sessions 
• Support and coach junior team members and peers, contributing to their growth 
• Play an active role in shaping our data science culture and community 

What we’d like to see from you:

Must Have 

• Experience delivering machine learning or advanced analytics solutions with measurable impact 
• Proficient in Python and SQL, with practical experience in modelling, feature engineering, and evaluation 
• Strong problem-solving skills and ability to break down complex problems into data-driven approaches 
• Comfortable working collaboratively in cross-functional teams 
• Clear communicator with a passion for sharing insights and learning from others 
• A background in a quantitative discipline (e.g. Computer Science, Mathematics, Statistics, Engineering) or equivalent hands-on experience in applied machine learning 

Nice to Have 

• Experience working in regulated sectors such as insurance, banking, or financial services 
• Familiarity with tools like MLflow, model registries, or experimentation platforms 
• Understanding of basic CI/CD concepts or exposure to production ML workflows 
• Interest in generative AI or large language models (e.g. OpenAI, Vertex AI) 
• Awareness of responsible AI principles, such as fairness or explainability in models 

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.