Senior Data Analyst

Scale Media•Burbank, CA

7d•$100,000 - $125,000•Remote

About The Position

Scale Media is seeking a Senior Data Analyst, described as a "Data Detective" and "Customer Value Master," to join their fully remote team. This role focuses on understanding the entire customer journey, from initial ad exposure to repeat orders, and owning the performance data for Retention, Acquisition, and Content. The analyst will partner with various teams, including Retention, Media Buying, Amazon, and Creative, to connect acquisition spend and content performance to long-term customer value. The company, Scale Media, has a proven track record of scaling wellness brands profitably and is investing in data and AI to enhance product development and brand scaling. They value ownership, feedback, thoughtful execution, clear communication, accountability, and trust, offering significant growth opportunities.

Requirements

5+ years of Data Analysis experience, with significant time in DTC, subscription, or consumer marketing analytics.
Hands-on experience building and deploying churn, LTV, or propensity models (e.g., logistic regression, survival analysis, gradient boosting) used for business decisions.
Proven experience in DTC E-commerce.
Fluency in Shopify, Amazon Seller Central, and Klaviyo data schemas.
Expert SQL in Snowflake.
Strong Python (pandas, scikit-learn, statsmodels, or similar).
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.
Understanding of the difference between pixel data, server-side tracking, and ad-platform reported data, and ability to explain discrepancies between ad platform revenue and e-commerce platform revenue.
Experience designing or analyzing conversion lift tests and understanding incrementality (ideally using a measurement tool like WorkMagic, Lifesight, or Measured).
Deep understanding of Klaviyo and Loyalty Lion data, including the impact of deliverability and Apple's Mail Privacy Protection (MPP) on lifecycle metrics.
Ability to differentiate creative that drives cheap clicks from creative that drives high-LTV customers.
Comfort with subscription metrics (MRR, churn rate, retention curves, payback periods).
Patience and precision to trace a single customer's journey from first ad click through various engagement points to their true lifetime value.

Responsibilities

Build, validate, and maintain churn, predicted LTV, and purchase propensity models, and ensure their regular use by retention and acquisition teams.
Develop customer segmentation to inform targeting, offers, and bidding strategies.
Monitor model performance over time and retrain models as customer behavior changes.
Analyze data from CRM and loyalty platforms (Klaviyo, Loyalty Lion) to provide insights on LTV, repeat purchase rates, and cohort degradation.
Define and maintain logic for 'active vs. lapsed vs. churned' customers for both subscription and one-time purchasers.
Measure the incremental impact of email, SMS, and loyalty programs, including conducting holdout testing.
Analyze paid acquisition across Meta, Google, TikTok, and Amazon Ads to provide insights on ROAS, CAC, payback, and new-customer quality.
Design and interpret incrementality and lift tests, and utilize marketing measurement platform (e.g., WorkMagic) and MMM outputs for budget allocation guidance.
Explain discrepancies between ad platform, attribution, and Shopify/Amazon data to media buyers.
Analyze ad creative and content performance (hooks, formats, angles, landing pages, video engagement) to identify drivers of efficient acquisition.
Connect creative-level data to conversion and retention outcomes, beyond top-of-funnel metrics.
Provide creative and content teams with clear, repeatable insights on performance, fatigue, and testing opportunities.
Prepare data using dbt or Python for retention, acquisition, and creative analysis datasets.
Write efficient SQL in Snowflake that reflects specific business rules.
Design, build, and maintain dashboards in Sigma for consistent performance views for each team.
Present findings and recommendations to marketing and growth leadership.
Review other analysts' work and share modeling best practices.