Sr Data Analyst (Retention Focus)
Trafilea
What You'll Do
Analyze & Uncover Insights
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
Model & Predict
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
Apply regression and time-series models to forecast retention and repeat revenue trends
Automate & Scale
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
Partner with the Business
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
Proactively surface insights that improve customer experience and long-term value
Share Knowledge
Document retention methodologies, analyses, and models
Mentor junior analysts on lifecycle analytics best practices
Help establish analytical standards for retention and customer insights
Why Trafilea
We’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.
Technical 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 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.)
Technical Skills (Nice to Have)
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
Soft Skills
Analytical mindset: Structured, hypothesis-driven problem solver
Communication: Translate customer data into clear business narratives
Business acumen: Strong understanding of unit economics and LTV impact
Proactivity: Identifies retention opportunities without being asked
Collaboration: Works cross-functionally with Growth, CRM, Product, and BI
Attention to detail: High standards for data quality, documentation, and reproducibility
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