Staff Data Scientist - Paid Marketing Optimization
Core
Design and develop a Creative Analytics framework, predict conversion lags, optimize bidding signals, and create uplift models to improve marketing efficiency and ROI across paid channels.
Role type
Staff Data Scientist (Paid Marketing Optimization)
Builds
Creative performance models, conversion-lag prediction models, value-based bidding signals, and customer uplift models for ad networks.
Domain
Ed-Tech / Paid Marketing / Attribution
Deliverable
production ML models
Required skills
Python, SQL, Spark, Databricks, Propensity modeling, Uplift modeling, Causal inference, Experiment design, Marketing attribution, Bidding platform mechanics
Preferred skills
Experience with ads ML, Recommender systems, Creative analytics
Technologies
Databricks, Spark, Google Ads, Meta Ads
Responsibilities
Design and develop the Creative Analytics framework; Predict conversion lags to minimize steering delay; Optimize bidding signals for Google and Meta; Create customer uplift models for audience optimization; Collaborate with Data Engineering and Applied AI on scalable data pipelines.
Seniority
Staff, hands-on IC with strategic impact
