Lead Marketing Data Scientist
Hybrid · Salt Lake City, Utah, United States
Job Summary
Lead Marketing Data Scientist to architect and optimize data pipelines linking marketing platforms to core business metrics, owning MMM, incrementality testing, geo-lift studies, and scenario analyses. Role sits at the intersection of marketing, data engineering, and growth strategy, translating signal data into actionable business decisions and driving media spend optimization. Responsibilities include designing data architectures, building unified marketing data layers, implementing MMM frameworks, conducting experiments across multiple channels, and delivering self-serve analytics products to inform leadership and cross-functional partners.
Required Qualifications
- 7+ years of experience in data science, marketing analytics, or quantitative marketing, with at least 3 years focused on performance marketing measurement.
- Experience working with AWS in Cloud data platform.
- AI/ML based LTV prediction experience to build predictive models that help achieve business outcomes.
- Proven track record of building and deploying Marketing Mix Models (MMM): Bayesian (e.g., Robyn, Meridian, LightweightMMM, PyMC) or frequentist in production environments.
- Hands-on experience designing and analyzing incrementality tests, geo-lift studies, and causal inference experiments (synthetic control, difference-in-differences, uplift modeling).
- Strong programming skills in Python (pandas, NumPy, scikit-learn, statsmodels, PyMC / Stan) and SQL; comfortable working with large-scale datasets.
- Deep, hands-on experience with at least one major cloud data platform (Snowflake, BigQuery, Databricks, Redshift) and modern data stack tooling (dbt, Airflow, Fivetran, or equivalent).
- Strong working knowledge of digital media and performance platforms including Google Ads, Meta Ads, programmatic DSPs, affiliate platforms, call tracking, and attribution tools.
- Experience operating in a SaaS, fintech, financial services, or other fast-paced, high-growth, performance-driven environment.
- Excellent communication and storytelling skills with the ability to influence senior stakeholders and translate analytics into business action.
- Bachelor’s degree in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science, Engineering, or related field).
- Preferred: Master’s or Ph.D. in Statistics, Econometrics, Data Science, or related quantitative field.
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