As a Senior Product & Growth Data Scientist, you'll be a key driver of how data shapes our product and growth decisions. You’ll combine product analytics, experimentation, and applied statistical / ML modelling to influence ZOE’s strategy, roadmap, and member experience.
You'll partner with product and growth teams to determine when descriptive analytics is sufficient and when predictive or causal models materially improve our ability to help members. We believe most decisions are reversible, so you'll balance statistical rigour with pragmatism — helping us move forward with ~70% evidence and iterating as we learn.
At ZOE, we're on a mission to empower people with the most advanced science and technology to transform their health. Data is at the heart of how we build products that deliver measurable health outcomes — and how we get those products in front of millions of people.
You'll sit within our Product & Growth Analytics team, a close-knit group of six experts where we pride ourselves on a diverse range of perspectives (our current split is 80% female and 20% male). You’ll work closely with closely with Product Managers, Growth Marketers, Designers and Engineers. The team combines analytics engineering, experimentation, and product data science — and you'll have a meaningful voice in how we raise the bar.
Optimise the growth journey: Analyse our acquisition funnel — from ad spend through quiz, signup, and activation — to find where we're leaking users and where small changes compound into big wins. Help us reach millions efficiently.
Run high-quality experiments: Design and analyse experiments across product and growth surfaces. Bring statistical rigour — (sequential testing, CUPED, uplift) to help us learn faster without sacrificing quality.
Shape strategy through metrics: Build and evolve metrics across acquisition, activation, engagement, retention, and monetisation. Surface the risks and leverage points that change what we prioritise.
Predict & Influence User Behaviour: Use causal and inferential methods (e.g., uplift modelling, regression, survival analysis) to move beyond "what happened" to "why." Develop lightweight ML models and segmentations that identify the specific levers driving long-term retention, conversion, and LTV.
Collaborate with Leadership: Act as a trusted analytics partner for the growth domain. You’ll communicate complex insights to senior stakeholders (including the C-suite), providing the data-driven confidence needed to shape company strategy.
Elevate our foundations: Work with dbt and our instrumentation layers to ensure the data we rely on is high-quality. You’ll help design data systems that serve multiple use cases across the team.
Apply a "So What?" Filter: We value clarity over complexity. You’ll be empowered to choose the simplest effective solution and pivot quickly when a hypothesis is disproven.
5+ years of experience in product analytics, growth analytics, data science where you have owned analytics domains and influenced product intent.
Strong quantitative foundation — whether through a degree (Statistics, Maths, CS, Engineering, Physics, Economics, or similar) or a track record of working through genuinely complex quantitative problems
Deep proficiency in SQL and Python, with hands-on experience in statistical modelling(e.g.; regression, classification, or time-to-event analysis).
Experience running rigorous experimentation and a clear point of view on what good looks like.
Familiarity with LTV, churn, retention, or conversion modelling — and translating predictions into concrete product or marketing interventions
The ability to translate complex technical findings into clear, actionable stories for stakeholders. You are comfortable sharing your perspective, even when it challenges the status quo.
You thrive in dynamic environments and are comfortable making recommendations with imperfect signals.
Thrive in fast-moving, low-process environments; aligned with our #ActFast value and comfortable acting on ~70% evidence
While not required, we’d love to hear about any experience you have with:
Subscription-based business models or consumer-facing products.
Measuring the impact of marketing spend (MMM, attribution or incrementality).
Working with mobile or app-centric data environments.
We value your time as much as our own. We’ve designed a streamlined, 4-step process to get us from "Hello" to "Welcome to the team" as quickly as possible.
Step 1: 👋 Intro chat with Talent Team
A high-energy intro to see if our missions align. We’ll chat about your journey, what makes ZOE tick, and make sure the basics (role, impact, and expectations) are a match.
Step 2: 🧠 Hiring Manager Interview
A tactical conversation focused on your craft. We skip the generic scripts and dive straight into how you solve problems, your past wins, and the specific challenges this role is here to tackle.
Step 3: 🔄 The Remote Loop This is where we get into the details. Depending on the role and level, this stage consists of 2 to 4 focused interviews designed to assess different areas (e.g., technical skills, cross-team collaboration, or strategic thinking).
Step 4: 🎉 The Finish Line (Offer & Onboarding) If there’s a match, we don’t hang around. We’ll extend an offer, talk through equity and benefits, and get you ready for your ZOE onboarding journey. Let’s change the world’s health together.
The experience, skills, and attributes we’ve outlined are what we believe will help someone truly thrive in this role.
However, we understand that talent comes in many forms. If you are genuinely excited about ZOE's mission and this opportunity, please don't hesitate to apply—even if you don't meet every single requirement listed.
We fundamentally value potential and commitment above all else. We are dedicated to fostering growth and providing opportunities for you to learn and develop alongside us.