The opportunity

We believe in the balance between innovation and incremental changes and we invest in both. 

You'll own a structured, always-on programme of experimentation across our key digital surfaces: landing pages, assessment flows, activation, and onboarding, with a clear ambition to expand into post sales and lifecycle touchpoints as the programme matures.

You'll bring both the scientific rigour to run experiments that actually mean something, and the strategic instinct to know which experiments are worth running in the first place. You'll build a living, learnings-driven roadmap that feeds directly into what comes next.

What you'll do

Turn data and insight into sharper hypotheses

• Combine multiple signals — funnel analytics, behavioural data, session recordings, patient research, support themes — to develop a genuine point of view on why the experience is performing or underperforming
• Run structured discovery each quarter that directly changes at least one roadmap priority; not just 'here's what the data says' but 'here's what we should do about it'
• Write read-outs that go beyond the result: what did we learn about patient behaviour? What does this change about our next hypothesis? What did we rule out?

Build and own a structured experimentation programme

• Build a clear hypothesis and experimentation framework based on both qualitative and quantitative insight, and not doing it because “my gut told me so”.
• Sequence experiments deliberately: validate assumptions cheaply before committing to big builds; test the riskiest hypotheses first
• Maintain a clear, always-current view of what you're testing, why you're testing it, and what you expect to learn — not a backlog of ideas, but a coherent programme with a through-line
• Ensure every test has a purpose that maps back to a strategic question about the patient experience

Set experiments up to actually tell you something

• Write rigorous briefs: clear hypothesis, defined primary metric, pre-specified success criteria, correct sample size, and expected run time before running a test.
• Understand the difference between statistical significance and practical significance and never call a test early, on gut feel, or because the numbers look good in week two
• After every experiment, update the roadmap based on what you learned, not just what you planned; dead ends are as valuable as wins if you know what to do with them
• Build a compounding library of knowledge about what works on our surfaces such as patterns, principles, and reusable frameworks the whole team can draw on

Work cross-functionally to ship

• Collaborate with design, product managers, growth marketing, and clinical to move tests through from brief to launch without delays accumulating
• Flag dependencies and risks before they become blockers; communicate clearly enough that the team always knows where things stand

Who we're looking for

You think of experiments as a way to validate your thinking, not just a test. You don't have a list of things to try: you have a framework for how you decide what to test, in what order, and why. Your roadmap tells a story: here's our current strategic focus, here's the evidence behind it, and here's what we'll do next depending on what we learn.

You're statistically literate and uncompromising about it. You understand statistical power, sample size, significance, and confidence intervals, not as boxes to tick, but as tools you use to protect the integrity of your conclusions. You've told stakeholders "we can't call this yet" and held the line. You know that a poorly run experiment is worse than no experiment at all.

You're a systematic hypothesis builder. Before you test anything, you know what question you're answering, what you expect to happen, and what you'll conclude if the result goes either way. You don't start from "let's try this". You start from "here's what we believe, here's why, and here's how we'll know if we're wrong."

You synthesise insight across sources. You don't trust one metric or one data type. You combine quantitative funnel data with qualitative signals: user research, session recordings, support themes to build a richer picture of what patients are experiencing, and you use that to write better hypotheses.

You're obsessed with the 'so what'. Results without implications don't interest you. Every read-out you write answers the question: what do we now know that we didn't before, and how does it change what we do next?

You own outcomes, not just execution. You track the metric post-launch, diagnose what happened, and come back with a next bet and not just a wrap-up. When something doesn't work, you treat it as data, not a failure.

The scope

Today, you'll own experimentation across our core web surfaces — landing pages, quiz flows, and purchase funnels. This is the heartbeat of our digital acquisition and activation experience. Over time, the scope will extend into post sales and other touchpoints as we build a more connected, end-to-end view of patient optimisation.

You'll work at the intersection of growth marketing, product management, UX, research, and conversion strategy,  bringing both the analytical depth to run a credible programme and the patient empathy to know what's actually worth improving.