Senior Data Analyst

Scale Media builds and scales science-backed wellness brands and is investing in data and AI to improve product development and brand growth. The Senior Data Analyst will own analytics across customer retention, acquisition, and content performance, building predictive models, analyzing marketing and customer data, and delivering trusted insights to growth teams.

Responsibilities:

• Build, validate, and maintain churn, predicted LTV, and purchase propensity models, and get them into regular use by the retention and acquisition teams
• Develop segmentation that informs targeting, offers, and bidding strategy
• Monitor model performance over time and retrain as customer behavior shifts
• Analyze data from our CRM and loyalty platforms (Klaviyo, Loyalty Lion) to provide granular insights on LTV, repeat purchase rates, and cohort degradation
• Define and maintain "active vs. lapsed vs. churned" logic for both subscription and one-time purchasers
• Measure the true incremental impact of email, SMS, and loyalty programs, including holdout testing
• Analyze paid acquisition across Meta, Google, TikTok, and Amazon Ads to provide granular insights on ROAS, CAC, payback, and new-customer quality
• Move beyond "last-click." Design and read incrementality and lift tests, and use our marketing measurement platform (e.g., WorkMagic) and MMM outputs to guide budget allocation
• Explain the gaps between ad platform, attribution, and Shopify/Amazon data clearly to media buyers
• Analyze ad creative and content performance (hooks, formats, angles, landing pages, and video engagement) to identify what drives efficient acquisition
• Connect creative-level data (e.g., Motion) to conversion and retention outcomes, not just top-of-funnel metrics
• Give the creative and content teams a clear, repeatable read on winners, fatigue, and what to test next
• Handle the "last mile" of data prep using dbt or Python to build the datasets behind retention, acquisition, and creative analysis
• Write efficient SQL in Snowflake that reflects our specific business rules
• Design, build, and maintain high-impact dashboards in Sigma that give each team a trusted, consistent view of performance
• Present findings and recommendations to marketing and growth leadership in a clear, compelling way
• Review other analysts' work and share modeling best practices across the team

Requirements:

• Experience Level: 5+ years of Data Analysis experience, with meaningful time in DTC, subscription, or consumer marketing analytics. (We are looking for a senior, hands-on individual contributor, not a people manager.)
• Hands-on experience building and shipping churn, LTV, or propensity models (e.g., logistic regression, survival analysis, gradient boosting) that the business used to make decisions. This is required
• Proven experience in DTC E-commerce is required. You must be fluent in Shopify, Amazon Seller Central, and Klaviyo data schemas
• Expert SQL in Snowflake, strong Python (pandas, scikit-learn, statsmodels, or similar), and proficiency with Sigma or a comparable BI tool
• Fluency with Claude Code (or comparable AI coding tools) for data manipulation and analytics
• Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function, so you can communicate effectively with our Data Engineer
• You understand the difference between pixel data, server-side tracking, and ad-platform reported data, and you can explain the discrepancy between Facebook Ads Manager revenue and Shopify revenue without blinking
• You have designed or analyzed conversion lift tests and understand incrementality (ideally using a measurement tool like WorkMagic, Lifesight, or Measured)
• You are deeply versed in Klaviyo and Loyalty Lion data, and you understand how deliverability and Apple's Mail Privacy Protection (MPP) distort lifecycle metrics
• You can tell a creative that drives cheap clicks from one that drives high-LTV customers
• You are comfortable with subscription metrics (MRR, churn rate, retention curves, payback periods)
• You have the patience and precision to trace a single customer's journey from first ad click through email opens, SMS clicks, and loyalty redemptions to their true lifetime value