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Careers at Eucalyptus

Digital User Experience Lead (CRO)

London
Posted about 23 hours ago
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About Eucalyptus

We're on a mission to make good health last a lifetime. More than 1 billion people live with obesity worldwide, driving preventable chronic conditions. We're here to build better long-term care.

Eucalyptus is now part of Hims & Hers, the global leader in personalised health and wellness.

Euc is the company behind Juniper, one of the world's largest weight-management programs combining GLP-1 medication with personalised nutrition, movement support, and clinician-led care from prescribers, nurses, health coaches, pharmacists, and dietitians. Our published clinical research shows that our combined clinical and behavioural approach helps patients lose significantly more weight during their treatment with Juniper by four times.

Our Growth Story

  • Supporting patients living with obesity across our 5 markets
  • Received selective NICE endorsement to provide services to the NHS
  • Tailored our offering to thousands of patients in Australia, the UK, Germany, Japan, and Canada.

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

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

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.

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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.

At Eucalyptus, we value individuals from all backgrounds, experiences, and perspectives, and we embrace the unique qualities each person brings. When you apply, please let us know of any reasonable adjustments you may need during the interview process. We use AI-assisted tools across our business to help our teams work more efficiently, including within our recruitment process. These tools support our team — all hiring decisions are made by real people, and every application is reviewed by a member of our recruitment team.

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Skills

Conversion Rate Optimization
Experimentation Frameworks
Statistical Analysis
Funnel Analytics
Hypothesis Testing
User Research
Product Management
Growth Marketing
Data Synthesis
Stakeholder Management
Behavioral Data Analysis
Strategic Planning
A/B Testing
Cross-functional Collaboration
Digital Product Strategy

Location

London, England, United Kingdom

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