Principal Data Scientist, Marketing Measurement

Candidates must possess a PhD or equivalent experience in statistics, econometrics, machine learning, or a related quantitative field, with a strong foundation in causal inference, experimental design, and Bayesian modeling. A minimum of 8 years of experience in data science or ML engineering roles is required, along with proven experience applying statistical methods to marketing measurement, attribution modeling, and incrementality/experiment design problems. Experience in building or optimizing large-scale A/B testing or experimentation infrastructure is essential, as is experience designing, deploying, and operating statistical/ML models that drive real business decisions at scale, including validation and monitoring. Proficiency in Python/R/SQL and modern data platforms like BigQuery or Snowflake is necessary, along with familiarity with MLOps practices and data pipeline orchestration tools. Strong communication skills to explain complex statistical concepts to customers and internal stakeholders are also required.