Own measurement and experimentation for customer activation and retention across CRM campaigns, promotions, onboarding, and next-best-action initiatives.
Responsibilities:
- Define metrics and evaluate initiatives using historical data.
- Design and analyse experiments end to end, including hypotheses, guardrails, audience splits, MDE, statistical power, stopping rules, and recommendations.
- Account for channel and engagement bias, and use causal inference methods when A/B testing is not feasible.
- Develop and launch experiments across onboarding and the customer lifecycle, and turn successful tests into recurring segmented flows.
- Build segmentation, propensity, churn, and dormancy models, including logic for next-best-action recommendations.
- Automate recurring analysis, audience refreshes, dashboards, and model workflows; connect engagement data back to the warehouse.
Requirements:
- Strong SQL and Python skills, and experience with Git-based warehouse workflows and code review.
- Defensible experiment design, statistics, and metric design.
- BI experience with Power BI, Tableau, or similar tools.
- Stakeholder management, business sense, ownership, and ability to communicate recommendations to non-technical audiences.
Nice to have:
- Causal inference methods and understanding of their appropriate use.
- Clustering and segmentation applied in production.
- Predictive modelling and uplift modelling.
- Braze or a comparable CRM platform.
Conditions and benefits: Remote or hybrid work across Europe, stock options, professional development, and access to the Work & Swim program in Cyprus.