Sr Data Analyst (Retention Focus)

What You'll DoAnalyze & Uncover InsightsConduct deep-dive analyses on retention, repeat rate, churn, cohorts, LTV, and lifecycle KPIsAnalyze customer behavior across the funnel (first purchase → repeat → loyal customer)Perform exploratory data analysis (EDA) to answer ad-hoc retention and lifecycle questionsIdentify drivers of churn and loyalty, delivering root-cause analysis with actionable recommendationsModel & PredictBuild 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 campaignsApply regression and time-series models to forecast retention and repeat revenue trendsAutomate & ScaleCreate Python/SQL scripts to automate recurring retention and cohort reportingBuild scalable data pipelines for customer lifecycle metricsDevelop QA processes to ensure accuracy and consistency in customer-level dataPartner with the BusinessTranslate retention and lifecycle business questions into technical analysesPresent insights clearly to non-technical stakeholders (CRM, Marketing, Growth, Finance)Collaborate with BI, Growth, and Lifecycle teams to define metrics and dashboardsProactively surface insights that improve customer experience and long-term valueShare KnowledgeDocument retention methodologies, analyses, and modelsMentor junior analysts on lifecycle analytics best practicesHelp establish analytical standards for retention and customer insights Why TrafileaWe’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.🚀 We build and scale our own brands.🦾 We invest in AI and automation like few others in eCom.📈 We test fast, grow fast, and help you do the same.🤝 Be part of a dynamic, diverse, and talented global team.🌍 100% Remote, USD competitive salary, paid time off, and more.RequirementsTechnical Skills (Must Have)Advanced SQL: Complex queries, CTEs, window functions; experience with data warehouses (BigQuery, Snowflake, Redshift)Python for Analytics: Pandas, NumPy; visualization libraries; automation scriptingStatistical Modeling: Regression, cohort analysis, time-series forecasting, hypothesis testingRetention & Lifecycle Analytics: Strong understanding of churn, retention curves, cohorts, LTV, repeat purchase behaviorData Visualization: Ability to build clear dashboards and charts; experience with BI tools (Looker, Tableau, Power BI, etc.)Technical Skills (Nice to Have)Experience with CRM or lifecycle channels (Email, SMS, Push, Loyalty programs)A/B testing and experimentation frameworks for retention initiativesIncrementality measurement for lifecycle campaignsE-commerce or DTC analytics backgroundSoft SkillsAnalytical mindset: Structured, hypothesis-driven problem solverCommunication: Translate customer data into clear business narrativesBusiness acumen: Strong understanding of unit economics and LTV impactProactivity: Identifies retention opportunities without being askedCollaboration: Works cross-functionally with Growth, CRM, Product, and BIAttention to detail: High standards for data quality, documentation, and reproducibilityOriginally posted on Himalayas