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As a Senior Growth Analyst, you’ll play a key role in driving data-led decision-making across the B2C side of the marketplace. Reporting into the Growth Analytics Lead, you’ll focus on understanding how drivers are acquired, how they interact and engage with our product, and what drives retention and increases lifetime value. This is a hands-on, impact-focused analytics role. The successful candidate will work closely with Marketing, CRM, Product and Engineering to translate data into clear, actionable insights that improve acquisition efficiency, engagement and lifetime value. You’ll own deep-dive analysis, lifecycle reporting and segmentation, while helping build scalable analytical assets that empower stakeholder self-service, proactive insight discovery and confident decision-making.
Job Responsibility:
Lead end-to-end growth analytics projects across the driver lifecycle — from problem definition through to insight delivery and clear, actionable next steps
Evaluate channel performance and LTV:CAC dynamics to inform marketing investment and targeting decisions
Conduct cohort, funnel and behavioural analysis to surface drivers of repeat usage, frequency and long-term engagement
Build and maintain growth-focused datasets, dashboards and analytical frameworks that enable stakeholders to self-serve answers and reduce reactive, ad-hoc analysis
Proactively explore data to inform strategy and guide investment decisions — not just respond to inbound request
Requirements:
3–5+ years’ experience in an analytics role, ideally within growth, marketing, product or commercial analytics, in a high growth environment
Strong SQL skills, with confidence working directly with large datasets in a modern data warehouse (Snowflake preferred)
Experience analysing funnels, cohorts, retention and user behaviour over time
Hands-on experience building dashboards or recurring reporting in Tableau (or a similar BI tool)
Experience working with web or marketing analytics tools such as GA4 (or another web analytics platform)
Nice to have:
Experience working with marketing or acquisition data (paid channels, attribution concepts, campaign measurement)
Familiarity with CRM or lifecycle analytics (segmentation, engagement, repeat behaviour)
Exposure to experimentation or A/B testing analysis
Experience applying data science techniques, such as predictive or propensity modelling, in a business context