Responsibilities

• Lead the design and analysis of large-scale experiments to measure advertising effectiveness across Amazon's advertising products
• Develop novel causal inference and econometric methodologies to solve attribution and incrementality measurement challenges at scale
• Invent new optimization frameworks that translate measurement insights into actionable bidding, targeting, and budget allocation strategies for advertisers
• Define the long-term science roadmap for ads measurement and optimization, identifying high-impact research directions and driving alignment across engineering, product, and science teams
• Build and refine structural and reduced-form models that quantify the causal impact of advertising on consumer behavior, sales, and brand outcomes
• Partner with engineering teams to operationalize econometric models into production systems serving millions of advertisers
• Mentor and develop a team of economists and applied scientists, raising the bar on methodological rigor and scientific impact
• Influence senior leadership through clear communication of complex economic concepts, shaping investment decisions and product strategy
• Collaborate cross-functionally with product managers, engineers, and business leaders to translate business problems into well-defined economic questions with scalable solutions

Requirements

• PhD in Economics, Computer Science, or highly related field (Statistics, Finance, Math)
• 10+ years in industry, consulting, government, or academic research
• Experience with big data and machine learning or data science
• Coding ability in a scripting language such as R or python or STATA

Preferred

• Experience in developing and executing an analytic vision to solve business-relevant problems.
• Experience in building analytic or scientific data products or solutions.
• Written and verbal communications skills to convey complicated process and systems to business partners and senior leadership.
• Applicants with considerably more and broader, experience, are also strongly encouraged.
• Strong track record in performing high-quality analysis of data at scale.