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Senior Product & Growth Data Scientist
🚀 The Big Picture
As a Senior Product & Growth Data Scientist, you'll be a key driver of how data shapes ZOE’s product and growth decisions. You’ll combine product analytics, experimentation, and applied statistical/ML modelling to influence the company’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 can materially improve our ability to drive member outcomes. We value strategic pragmatism—you’ll balance statistical rigour with real-world decision-making, helping us move forward with ~70% evidence while iterating as we learn.
👥 The Squad
At ZOE, we empower people to transform their health using advanced science and technology. Data is the backbone of our product development and growth strategy—helping us build solutions that deliver measurable health outcomes for millions.
You’ll join our Product & Growth Analytics team, a tight-knit group of six data experts with a diverse range of perspectives (currently 80% female, 20% male). You’ll collaborate closely with:
- Product Managers
- Growth Marketers
- Designers
- Engineers
The team excels in analytics engineering, experimentation, and product data science—and you’ll play a meaningful role in raising the bar.
🎯 Your Mission
Optimise the Growth Journey
- Analyze our user acquisition funnel—from ad spend to quiz completion, signup, and activation—to identify leaks and opportunities where small optimisations deliver compounded growth.
- Help scale efficiently to reach millions of members.
Run High-Impact Experiments
- Design and analyse rigorous experiments across product and growth surfaces.
- Apply statistical techniques (sequential testing, CUPED, uplift modelling) to accelerate learning without compromising quality.
Shape Strategy Through Data-Driven Metrics
- Build and iterate metrics across:
- Acquisition
- Activation
- Engagement
- Retention
- Monetisation
- surface risks and leverage points that directly influence prioritisation.
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Predict & Influence User Behaviour
- Use causal inference (uplift models, regression) and time-series analysis to move beyond "what happened" to "why."
- Develop lightweight ML models and segmentations to:
- Identify high-leverage drivers of retention, conversion, and LTV.
- Inform concrete product and marketing interventions.
Collaborate at Executive Level
- Serve as a trusted analytics partner to growth leadership.
- Present complex insights to senior stakeholders (including the C-suite) with clarity and confidence.
- Drive data-driven decision-making at the strategic level.
Strengthen Data Foundations
- Work with dbt and instrumentation layers to ensure high-quality data.
- Design data systems that support multiple business needs across the team.
🧠 Your DNA
Core Experience:
- 5+ years in product analytics, growth analytics, or data science, where you’ve:
- Owned analytics domains.
- Influenced product strategy directly.
- Strong quantitative foundation, whether through:
- A degree (e.g., Statistics, Maths, CS, Engineering, Physics, Economics).
- A proven track record in complex problem-solving.
- Deep hands-on expertise in:
- SQL (intermediate to advanced).
- Python (with libraries like Pandas, StatsModels, PyMC3).
Key Technical Skills:
- Statistical modelling (regression, classification, survival analysis).
- Causal inference (e.g., prophet, instrumental variables, horror model).
- Experimentation: Design and analyse A/B tests rigorously.
- Retention, LTV, or churn modelling—and translating predictions into action.
- Familiarity with metric definitions (e.g., MAU, DAU, monetisation KPIs).
Soft Skills:
- Ability to simplify technical findings for non-technical stakeholders.
- Comfort articulating challenging perspectives—and advocating for data over assumptions.
- Thrives in ambiguity—comfortable acting on imperfect signals.
- Fast-moving environments align with our "#ActFast" values.
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Nice to Have:
- Experience with subscription-based models or consumer products.
- Incrementality/attribution analysis (e.g., MMM techniques).
- Mobile/app data environments.
✨ Our Hiring Journey
We respect your time. A streamlined 4-step process ensures we move from "Hello" to "Welcome" quickly:
Step 1: 👋 Intro Chat
- High-energy discussion to align expectations.
- Your career journey.
- Mission fit with ZOE.
- Confirm the role’s key elements: impact, scope, and requirements.
Step 2: 🧠 Craft-Specific Interview
- Focus on practical problem-solving—not generic Q&A.
- Explore:
- Past successes.
- Your approach to challenges.
- How your work directly influences growth/product decisions.
Step 3: 🔄 The Remote Loop
- 2–4 focused interviews tailored to this level (e.g., technical skills, cross-team collaboration).
- Mapped to associated impact areas relevant to the role.
Step 4: 🎉 Offer & Onboarding
- Swift close: offer extended promptly.
- Cover equity, benefits, and global onboarding.
- Start making an impact immediately.
🚀 Ready to Thrive?
The experience and attributes outlined here are designed to maximise fit for this role. But we understand that talent comes in many forms. If you’re genuinely excited by ZOE’s mission and this opportunity:
🔹 Apply even if you don’t meet every box—storytelling matters. 🔹 We value potential, character, and commitment above rigid requirements.
At ZOE, we’re committed to growth—and we’ll help you develop alongside us. [Let’s change the world of health together.](link בשנת ה" kiểm tra đảm bảo tráfico vào trang) 🌱
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