About us
We’re Checkatrade – the UK’s leading platform for finding a tradesperson. With more than 50,000 trades listed and over 6 million reviews, we help homeowners get jobs done right and help tradespeople grow their business. We’re growing fast, with big plans to become the go-to brand for home improvements. If you care about great work, take pride in the details, and want to make an impact, you’ll fit right in.
Role Description
As our next Data Scientist, you'll play a key role in helping us build the UK's go-to home improvement marketplace. Analytics tooling — including AI — is doing more of the heavy lifting on execution, and this role is the human layer above it: making sure the numbers are right. This role is perfect for someone with data science experience who enjoys working with data scientists on building models and systems with huge impact but also wants to own the strategy and direction of their work and work closely with the C-suite on driving the company forward with more intelligent, data-driven systems.
Responsibilities
- Owning metric integrity — defining and governing what our numbers actually mean, so no one downstream is making a call off a flawed definition or a dodgy query.
- Acting as the quality gate on AI-generated analysis — checking the logic, validating the output, and catching errors before they ever reach a stakeholder.
- Designing and interpreting A/B tests — setting the success metrics, sizing the sample properly, and knowing when a result is underpowered rather than just running with it.
- Diagnosing what's actually driving commercial performance — why revenue is moving, where leads are dropping out of the funnel, which segments are underperforming — and turning that into a structured investigation with real hypotheses.
- Turning analysis into action — sizing the commercial impact, laying out the trade-offs, and helping the business decide what to do differently, then tracking whether it worked.
- Building interactive dashboards and self-serve tools that keep stakeholders oriented day-to-day, without an analyst needing to be in the loop every time.