Data Scientist, Growth & Measurement

Role Overview

Comfrt is hiring a Data Scientist, Growth & Measurement to build the analytical foundation for marketing measurement, incrementality, and growth economics. You will own measurement systems, experimentation frameworks, and modeling capabilities that inform how Comfrt allocates spend and evaluates long-term value.

Responsibilities

Measurement & Causal Inference

• Own and evolve Comfrt’s measurement framework with partners across MMM & MTA (Northbeam) and incrementality (Workmagic)
• Lead Marketing Mix Modeling (MMM) initiatives with measurement partners and internal stakeholders
• Design and evaluate geo tests, holdouts, lift studies, and quasi-experimental frameworks
• Quantify true incremental impact across channels, campaigns, creators, and growth initiatives
• Identify saturation points, diminishing returns, and marginal efficiency curves
• Improve model accuracy, interpretability, and decision reliability

Growth & Customer Economics

• Build models to improve CAC efficiency, LTV forecasting, contribution margin visibility, and retention economics
• Analyze customer cohorts to find drivers of high-value and durable behavior
• Partner with Growth and Finance on forecasting, budget allocation, and investment planning
• Separate short-term performance from long-term brand and customer value
• Develop frameworks tying acquisition, retention quality, and enterprise value

Data & Decision Systems

• Build scalable, production-grade models and analytical systems using Python and SQL
• Work with Data Engineering/Analytics to improve data quality, metric governance, and experimentation infrastructure
• Standardize trusted business metrics (e.g., CAC, LTV, MER, contribution margin, retention, incremental ROI)
• Collaborate with Engineering/BI to operationalize models into dashboards, workflows, and reporting

Strategic Influence

• Translate analyses into actionable recommendations for growth investments and profitability
• Partner cross-functionally across Growth, Finance, Product, Data Engineering, and Technology
• Help establish a culture of rigorous, data-informed decision-making

Requirements

• 4–7+ years of experience in marketing science, econometrics, experimentation, or applied data science
• Deep experience with:
  • Marketing Mix Modeling (MMM)
  • Causal inference and incrementality testing
  • Statistical modeling and experimentation design
  • Regression, time-series, Bayesian, and/or forecasting methods
• Strong understanding of growth economics, customer behavior, and marketing efficiency
• Advanced Python and SQL
• Experience with large-scale marketing and transactional datasets
• Familiarity with modern data warehouses: Snowflake, BigQuery, or Redshift
• Strong communication skills

Nice-to-haves

• None explicitly stated beyond the listed tooling/warehouse familiarity and communication skills.