Senior Marketing Data Scientist

Senior Marketing Data Scientist

Department: Data & Analytics

Employment Type: Full Time

Location: Cardiff

This is a hybrid role. You'll be expected to join us at one of our main hubs (London or Cardiff) approximately twice a month for key team meetings, workshops, and planning sessions.

About us: In 2002, we became the first insurance comparison site. Our purpose? To make the process of sorting your insurance, utilities or personal finances as easy as possible.

We’re part of RVU. A group of online brands that include Uswitch, Tempcover and  As a group, we use our shared knowledge to empower people, and help them make decisions confidently across a range of household services.

is at the cutting edge of the Fin Tech industry, so we’re always looking for extraordinary talent. If you love what you do, get in touch today!

As a Senior Marketing Data Scientist at , you will be a crucial driver of business impact, bridging the gap between complex data and strategic marketing decisions.

In this role, we are looking for a strategic analytical leader who will quantify the effectiveness of our marketing strategy. You will partner closely with Marketing, Finance, and leadership to optimise our multi-million pound marketing budget and shape the future of our growth.

This isn't just a maintenance role; it's a strategic challenge. Our analytics function is on a mission to evolve from a reactive reporting team into a proactive, value-generating engine, and this role is fundamental to that shift.

You will be a key architect of this change, bringing the critical causal inference expertise needed to elevate our team's technical standards and help us generate new, high-value ideas directly from our data.

Reporting to our Head of Analytics, you will join our central Data Science team
, a high-impact group of specialists that functions as an internal centre of excellence.

• What is the true incremental impact of our TV advertising on car insurance sales?
• How should we reallocate our budget between different marketing channels to maximize ROI?
• What is the true impact of our promotional offers on customer acquisition and retention?
• Which customer segments are most responsive to our marketing efforts and why?

• Take ownership of a critical, high-value, and high-visibility process that determines our ad spend.
• Design, build, and maintain advanced Marketing Mix Models to inform strategic budget allocation.
• Apply causal inference techniques to measure the incremental impact of specific marketing campaigns and initiatives.
• Partner with senior stakeholders to translate complex model outputs into clear, actionable recommendations for leadership.
• Champion and build greater team autonomy by designing robust, source-controlled data pipelines for marketing data products.
• Mentor and up-skill our wider analytics team, in the principles of experimental design and causal inference, helping to level-up the entire team.

• You have an expert-level SQL and Python skills for large-scale data analysis and model development.
• You have a deep understanding of causal inference methodologies (e.g., DiD, PSM/IPW) and advanced experimental design (A/B/n testing).
• Ideally, you have proven experience developing and deploying Marketing Mix Models in a commercial environment.
• Strong statistical foundation, ideally including Bayesian methods.
• A passion for building production-quality, source-controlled data products, with data engineering skills to help the team own more of its data pipelines.
• Exceptional stakeholder management and influence, with a demonstrated ability to translate complex quantitative concepts for senior, non-technical audiences.
• An ambassador for data, who can advocate for data-driven decisions across multi-disciplinary teams.
• A growth mindset and a passion for mentoring, with a desire to help raise the entire team's technical standard.

• 10% discretionary yearly bonus and yearly pay reviews (based on RVU and personal performance)
• A fully remote working approach with the option to "work from anywhere" for up to 22 working days per year.
• Employer matching…