Principal Applied Scientist

What you'll do

• Define and drive scientific and technical strategy for data-driven attribution and causal measurement across advertising systems
• Establish methodologies for incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction
• Lead design and production adoption of attribution and causal inference frameworks to improve bidding, ranking, optimization, and advertiser ROI
• Set evaluation standards to distinguish correlation from causation and elevate experimental rigor
• Identify capability gaps and introduce advanced research, tools, or modeling approaches
• Operate across organizational boundaries to align research, engineering, product, and business leaders on measurement strategy
• Serve as subject-matter expert and technical advisor on attribution and causal inference
• Mentor scientists and influence technical direction to raise scientific bar

Requirements

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
• OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
• OR equivalent experience
• Preferred: Master's Degree AND 9+ years related experience or Doctorate AND 6+ years related experience or equivalent
• Demonstrated track record of setting technical direction for large-scale machine learning or statistical systems
• Deep expertise in causal inference, data-driven attribution, treatment effect estimation, counterfactual learning, or experimental design in production
• Experience leading ambiguous, high-impact initiatives with limited ground truth and methodological rigor
• Proven ability to influence strategy and drive adoption of new measurement or modeling approaches
• Significant experience developing and deploying production ML systems across product lifecycle
• Solid scientific judgment selecting appropriate methodologies under real-world constraints
• Exceptional communication skills for technical and business leaders
• Recognized expertise in attribution, incrementality, marketplace experimentation, or causal ML
• Track record of driving multi-year research or modeling agendas improving product outcomes
• Experience defining measurement strategy for advertising platforms, marketplaces, or recommendation systems
• Publications, patents, or widely adopted internal methodologies in causal inference, experimentation, econometrics, or applied ML
• History of mentoring senior scientists and elevating organizational scientific capability
• Experience influencing director- or VP-level technical strategy

Tech stack

Benefits