Senior Data Analyst – Retention Focus
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Job Description
Data Analyst focusing on retention analytics for a tech-led eCommerce group involved in building and scaling globally loved DTC brands. Collaborating with various teams to deliver insights and improve customer experience.
Responsibilities:
- Conduct deep-dive analyses on retention, repeat rate, churn, cohorts, LTV, and lifecycle KPIs
- Analyze customer behavior across the funnel (first purchase → repeat → loyal customer)
- Perform exploratory data analysis (EDA) to answer ad-hoc retention and lifecycle questions
- Identify drivers of churn and loyalty, delivering root-cause analysis with actionable recommendations
- Build and maintain cohort-based and predictive models (churn prediction, LTV forecasting)
- Design and analyze A/B tests and lifecycle experiments (email, SMS, loyalty, offers, timing)
- Support incrementality measurement for retention initiatives and CRM campaigns
- Create Python/SQL scripts to automate recurring retention and cohort reporting
- Build scalable data pipelines for customer lifecycle metrics
- Develop QA processes to ensure accuracy and consistency in customer-level data
- Translate retention and lifecycle business questions into technical analyses
- Present insights clearly to non-technical stakeholders (CRM, Marketing, Growth, Finance)
- Collaborate with BI, Growth, and Lifecycle teams to define metrics and dashboards
- Document retention methodologies, analyses, and models
- Mentor junior analysts on lifecycle analytics best practices
- Help establish analytical standards for retention and customer insights
Requirements:
- Advanced SQL: Complex queries, CTEs, window functions; experience with data warehouses (BigQuery, Snowflake, Redshift)
- Python for Analytics: Pandas, NumPy; visualization libraries; automation scripting
- Statistical Modeling: Regression, cohort analysis, time-series forecasting, hypothesis testing
- Retention & Lifecycle Analytics: Strong understanding of churn, retention curves, cohorts, LTV, repeat purchase behavior
- Data Visualization: Ability to build clear dashboards and charts; experience with BI tools (Looker, Tableau, Power BI, etc.)
- Experience with CRM or lifecycle channels (Email, SMS, Push, Loyalty programs)
- A/B testing and experimentation frameworks for retention initiatives
- Incrementality measurement for lifecycle campaigns
- E-commerce or DTC analytics background
Benefits:
- USD competitive salary
- paid time off
- professional development opportunities
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