Senior Data Scientist
Location
United Kingdom
Posted
67 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist
ZOE.COM
• 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.
Job Requirements
- 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.
Benefits
- Health insurance
- Flexible working hours
- Professional development opportunities
- Paid time off
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