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Remote, mid-level generalist Data Scientist in a metro market increases candidate competition.
Core data science and tooling are transferable, though ad-tech audience experience is beneficial.
Explicit 5+ years, Databricks/Spark/Snowflake, statistical and production model experience required.
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Build and validate statistical and ML models to create, expand, and score audience segments using multi-source data (survey, purchase, media).
Lead data fusion combining deterministic and probabilistic sources into consumer views while correcting biases.
Own audience measurement analytics (reach, overlap, index strength, incremental lift) and collaborate with ML Engineers for production deployment under privacy-by-design principles.
Approximately 5+ years experience in applied data science with models deployed in production or client delivery.
Proficient in statistical modeling techniques including survey stats, causal inference, experimental design, propensity/uplift models.
Working knowledge of Databricks, Spark, Snowflake, strong Python (pandas, scikit-learn, statsmodels), and SQL with large databases.
Degree required in a quantitative field such as Statistics, Data Science, Economics, Computer Science, or Math.
Experience in media or advertising domain or exposure to audience/identity or ad tech (DSP/SSP, DMP/CDP, clean rooms, identity graphs).
Ability to handle complex multi-source data integration and bias correction for consumer audience modeling.
Familiarity with privacy-preserving data collaboration methods and regulations like GDPR and CCPA.