Staff Data Scientist

Staff Data Scientist

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Compare The Market Limited

At a Glance

  • Tasks: Lead high-impact AI solutions and mentor fellow data scientists in a dynamic environment.
  • Company: Join Compare the Market, a purpose-driven tech company transforming financial decisions.
  • Benefits: Hybrid work, inclusive culture, and opportunities for personal and professional growth.
  • Other info: Embrace challenges and thrive in a fast-paced, results-oriented workplace.
  • Why this job: Make a real difference with cutting-edge AI while collaborating with diverse teams.
  • Qualifications: Experience in ML/AI, strong Python skills, and a passion for innovation.

The predicted salary is between 70000 - 90000 £ per year.

Curious about what’s next? So are we. Join Compare the Market and help to make financial decisions 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.

As the Staff Data Scientist, you will deliver high‑impact AI and decisioning solutions while raising the bar for how we discover, experiment, develop and productionise ML and AI models at Compare the Market. You’ll partner closely with product, engineering and machine learning engineering to take the most important use cases from problem framing and research through to robust, measurable value in production. Set technical direction for complex initiatives, mentor other data scientists, and champion responsible, scalable practices across the model lifecycle.

Some of the great things you’ll do:

  • Data Science Strategy & Delivery: Lead mission‑critical data initiatives from discovery to deployment and continuous improvement, with clear success metrics and guardrails. Tackle complex, ambiguous problems through research, structured experimentation, modelling and optimisation; reduce risk through iterative hypotheses and A/B and/or multivariate tests. Define the technical approach and roadmaps for high‑priority use cases within a domain using a range of paradigms and frameworks (e.g. supervised, unsupervised, reinforcement learning, foundation models); align with Product & Engineering to deliver outcomes to agreed timelines and quality standards.
  • Modelling, Productionisation & Standards: Apply and contribute to best practices for experimentation, modelling and measurement (including uplift/causal methods), ensuring reproducibility, versioning and lineage. Review and raise the standards on critical models (e.g. feature engineering, validation, bias/leakage prevention); translate research into pragmatic, production‑ready methods. Partner with machine learning and AI engineers to productionise robust batch/real‑time services following best practices; embedding monitoring, drift detection, explainability and fairness standards.
  • Technical Leadership, Influence & Collaboration: Act as a technical coach and mentor across squads – mentoring time is supported; provide design/analysis reviews and uplevel senior ICs and early‑career talent. Influence roadmaps by collaborating with Product, Engineering and Data leaders on priorities and trade‑offs; represent Data Science in architecture and design forums. Contribute to the AI/ML platform direction by shaping requirements and partnering with platform owners; drive adoption of reproducible, reliable workflows.
  • Culture & Innovation: Foster a culture of learning, transparency and cross‑functional collaboration; share decisions, assumptions and outcomes openly. Evaluate emerging research and market trends (e.g., LLMs, recommender / optimisation methods, knowledge graph, transformers) and turn promising ideas into prototypes and patterns. Embed responsible AI in day‑to‑day delivery—explainability, fairness and compliance—and promote continuous improvement through demos and write‑ups.

What we’d like to see from you:

  • Proven experience delivering high‑impact ML/AI solutions in complex, data‑rich environments, including production deployment and post‑launch iteration.
  • Advanced hands‑on proficiency in Python and core DS/ML libraries; strong SQL and familiarity with distributed data tooling.
  • Strong understanding of experimentation and statistical inference; experience designing trustworthy A/B tests and measurement frameworks.
  • Strong grasp of ML system design and the model lifecycle (from discovery and experimentation through to deployment, monitoring and governance).
  • Ability to lead cross‑functional technical work with multiple stakeholders and to influence without authority.
  • Excellent communication and storytelling skills, able to convey complex ideas simply and align teams on decisions.
  • Experience mentoring other data scientists and shaping best practices across a team.
  • Background in a quantitative field (e.g., statistics, computer science, mathematics, engineering) or equivalent applied experience.

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.

Staff Data Scientist employer: Compare The Market Limited

At Compare the Market, we pride ourselves on being a purpose-driven employer that fosters a dynamic and inclusive work culture. Our hybrid London office offers a collaborative environment where you can thrive as a Staff Data Scientist, with ample opportunities for professional growth, mentorship, and the chance to make a tangible impact on millions of customers' financial decisions. Join us to be part of a high-performing team that values innovation, accountability, and continuous improvement.

Compare The Market Limited

Contact Details:

Compare The Market Limited Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Data Scientist

Get Involved in Data Science Meetups

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Show Off Your Projects

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Apply Directly through Our Website

When you find a suitable opening like Staff Data Scientist at Compare The Market Limited, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Staff Data Scientist

Machine Learning
Artificial Intelligence
Python
SQL
Statistical Inference
A/B Testing
Model Lifecycle Management

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Compare The Market Limited, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Compare The Market Limited. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Compare The Market Limited

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Compare The Market Limited!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.