Senior Applied Scientist

What you'll do

• Drive innovations in ad interaction outcome prediction under partial and noisy feedback.
• Design data-driven attribution pipelines and weak-label generation for robust learning methods.
• Develop multi-task models and proxy-signal frameworks, enhancing offline and online measurement.
• Translate modeling advances into production-ready systems impacting ad ranking and user experience.
• Improve advertiser ROI by refining conversion models and engagement predictions in large-scale ads.

What we're looking for

• 4+ years of industry experience building and shipping machine learning models in production.
• Experience with conversion, outcome, or funnel modeling including post-click and engagement issues.
• Familiarity with model calibration, reliability analysis, and uncertainty estimation in production systems.
• Background in causal inference, attribution, and counterfactual evaluation methods.
• Solid hands-on experience with modern ML models and feature engineering for large datasets.
• Proven technical leadership in cross-team modeling efforts or platform-level ML systems.
• Experience designing or operating multi-task / auxiliary-task learning systems.