Sr. Economist, Pricing Science
$159.2k - $215.3kAmazon Inc.
ID lavoro: 10414297 | Amazon.com Services LLC Amazon's 1P retail pricing systems make millions of automated decisions every day to deliver competitive prices to customers. As agentic shopping tools become more prevalent, we work to ensure these systems continue to produce efficient, customer-beneficial outcomes and avoid defects. We're hiring a Sr. Economist to help lead this effort. You'll develop the science for understanding how Amazon's pricing systems behave around our major promotional events and design mechanisms that improve long‑run customer value. The role sits at the intersection of economic theory, applied econometrics, and production systems — and requires someone who can operate independently across all three. Key job responsibilities Own the economic modeling of how our pricing systems behave during our major promotional events — characterizing when our automated decisions produce efficient outcomes versus persistent defects, and designing mechanisms to correct the latter Develop econometric identification strategies for measuring the impact of pricing defects and the value of proposed corrections Deliver high‑stakes analyses connecting pricing to customer trust and long‑run business outcomes at VP+ level Translate economic models into system‑level requirements that engineering teams can implement as automated safeguards Serve as cross‑team advisor to partner teams in Demand Science, Finance, and Product About the team P2OS is a 12‑person team of applied scientists and economists within WW Pricing & Promotions. We own the science behind Amazon's retail pricing decisions — optimization, demand estimation, price prediction, and error detection. The team values rigorous identification, clean problem framing, and work that changes how systems behave. You'll join a team that includes a Principal Economist, senior applied scientists, and dedicated experimentation leads — with direct access to pricing leadership.
- PhD in economics or equivalent
- 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
- 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
$159.2k - $215.3k
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