Senior Data Scientist

Compare the Market is shifting from a business that answers data questions to one that builds the intelligence powering our AI platform - signals detected, decisions shaped, actions triggered., * Lead ML and analytics initiatives end-to-end, from exploration through to deployment and monitoring, collaborating with ML Engineers on productionization.

• Translate business and customer problems into structured, measurable ML solutions.
• Design and interpret experiments and A/B tests with scientific rigor.
• Champion responsible, auditable AI - owning model performance in production, knowing when a system is degrading and how to address it, in a regulated financial services environment where precision and explainability matter.
• Navigate the tooling landscape: knowing when classical ML is right, when an LLM adds value, when an agentic approach is needed.
• Work with commercial, product, and engineering colleagues to scope and prioritize work, communicating outcomes clearly.
• Mentor junior data scientists and contribute to standards across the wider Data & AI Solutions chapter.

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., * Proven experience delivering ML solutions with measurable business impact.

• Strong Python and modeling fundamentals - supervised and unsupervised methods, statistical analysis, feature engineering.
• Track record of taking models to production and owning their performance: monitoring, degradation, retraining.
• Ability to collaborate effectively with engineering teams on deployment and ML lifecycle.
• Clear communication - able to make technical work legible to commercial and product audiences.

Highly Valued

• Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangChain or LangGraph.
• Familiarity with multi-step agentic AI patterns.
• Experience in financial services or another regulated sector.
• MLflow, model registries, or similar ML lifecycle tooling.
• Exposure to cloud ML platforms - GCP Vertex AI, AWS SageMaker, or equivalent.