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