Lead the implementation of variance reduction (CUPED) and sequential testing to increase platform sensitivity and speed.
Architect and deploy interleaving frameworks to rapidly assess ranking model performance in real-time.
Design methodologies to account for finite advertiser budgets and prevent experimental groups from cannibalizing each other's spend.
Research and validate surrogate metrics that correlate highly with long-term user retention and value.
Build the statistical foundations for automated pipelines that autonomously test and select optimal features and hyperparameters.
Serve as the lead subject matter expert on experimentation for ML, Product, and Engineering teams.

8+ years of experience in Data Science or Applied Research, specifically within Ad Tech, Marketplaces, or high-scale experimentation platforms.
An MS or PhD in a quantitative field (Statistics, Economics, Computer Science, Operations Research, or equivalent).
Deep expertise in causal inference, experimental design, and frequentist/Bayesian statistics, with a proven track record of applying these to high-volume, real-time data.
Strong programming skills in Python or Scala, and experience with large-scale data processing frameworks like Spark, Snowflake, or BigQuery.
Practical experience implementing advanced testing methodologies like CUPED, interleaving, or switchback testing in production environments.
Ability to translate complex statistical concepts into clear product roadmaps and mentor engineering teams on experimental rigor.

Senior Data Scientist

Key skills