Data Analysis Specialist

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

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

Proactively surface insights that improve customer experience and long-term value

Document retention methodologies, analyses, and models

Help establish analytical standards for retention and customer insights

We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.

• ##We invest in AI and automation like few others in eCom.
• ##We test fast, grow fast, and help you do the same.
• ##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: Regression, cohort analysis, time-series forecasting, hypothesis testing

Data Visualization: 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

Translate customer data into clear business narratives

Strong understanding of unit economics and LTV impact

Works cross-functionally with Growth, CRM, Product, and BI

High standards for data quality, documentation, and reproducibility