Sr. Economist, Pricing Science

Amazon • Seattle, WA

4d • Onsite

About The Position

Estimating the long-run customer value of a pricing decision is genuinely hard. The causal effects are delayed, noisy, and confounded by factors that standard experiment analysis wasn't designed to handle. Most pricing teams default to short-run metrics not because they don't care about long-run outcomes, but because measuring them rigorously is an unsolved problem. P2OS is building the science to solve it. We're hiring a Sr. Economist to own that work — defining how we estimate customer lifetime value in a pricing context, building the identification strategies that make those estimates credible, and translating outputs into something pricing teams can use to make better decisions. The role sits at the intersection of econometric methodology and production-quality analysis, and requires someone who can operate independently in both. As science lead, you'll own the LTV methodology domain, develop the economists and scientists on your scrum, and be the internal authority on causal inference for pricing across P2OS and partner teams.

Requirements

• PhD in economics or equivalent

Nice To Haves

• Experience in analytics and applied economics
• Experience in developing and executing an analytic vision to solve business-relevant problems
• Experience in building statistical models using R, Python, STATA, or a related software
• Experience in industry, consulting, government or academic research
• Experience with ML-adjacent causal methods (Double ML, causal forests, CATE estimation) and background in customer behavior modeling, LTV estimation, or long-run treatment effect estimation

Responsibilities

• Own the end-to-end LTV methodology for pricing — identification strategy, modeling choices, validation approach, and business use cases — and drive adoption across pricing contexts
• Deliver high-stakes analyses connecting LTV estimates to a concrete pricing decision and strategy change at VP+ level
• Apply advanced causal methods to live pricing problems; document approaches so the team can build on and extend them.
• Provide causal inference guidance on pricing experiment questions as they arise — being the methodology resource when experiments generate LTV-relevant questions
• Serve as cross-team economic advisor to Finance, Customer Behavior, and Demand Science on LTV assumptions and causal identification
• Actively mentor junior scientists, earn trust of cross-functional tech and product partners.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree