Principal Economist, P2 Optimization Science

How should Amazon adjust the customer experience (CX) based on the competitiveness of its prices? How can we balance between helping customers discover new products through lower prices, helping sellers promote, and being confident that our pricing consistently earns trust? Where should we show pricing depth versus selection breadth?

This role will be the technical leader developing the mental model and data to answer these and related questions. The long term goal will be to propose and implement mechanisms to improve the customer journey from a price perspective, helping to use prices to prioritize between products, determining which information is displayed on the product (and how), and using prices to personalize of the CX to save customers money and time. The role will drive prioritization and implementation by generating value estimates of the impact of alternative decisions. A key component of the role is to develop the framework to guide prioritization and the expected impact from the proposed improvements, and use it to align efforts across different teams within and outside of the organization. An important component of the role is therefore to understand and quantify where price has more impact than other aspects of the CX.

Most of the questions this role will advance are on the intersection of many other teams that contribute to the CX, and to Amazon’s price setting mechanisms. An important component of the role is to collaborate with the these science and product teams on improvements that will enable further optimization of the price-related CX. This role will be expected to drive several cross-org science and product initiatives, and be a significant contributor to others. Therefore, the role is expected to work closely with leaders and ICs across multiple orgs on scoping, planning, execution, and delivery.


Key job responsibilities
Today, we are missing a unified way to frame our traffic shaping actions in terms of their impact on the long-term customer CX. While we have conviction that we are doing the right thing, and our tenets are customer-obsessed, we lack the system which allows us to discern our interventions between good and great. This role will:

- develop a framework to connect our measurements of price perception (UPEF, surveys, specific defect measurements like FOD) to our actions to protect the customer experience (badging, promoting, delisting)
- produce quantifiable, explainable, measurements of good/bad CX which are used to calibrate this framework
- develop a scientific roadmap which prioritizes the development based on the opportunity of using these measurements
- partner with key scientific partners (Search, Stores Monetization) to stay connected to co-developments in related domains
- Deliver the capability to begin to optimize our traffic shaping program by connecting our measurement inputs (price quality, promotional signals) to our customer and seller outputs (pricing LTV, OPS/CP)



About the team
The Pricing and Promotions Optimization Science (P2OS) team is a small unit of specialized science resources with deep expertise in optimization, machine learning, and microeconomics. We are equipped to solve some of the organization’s most ambiguous challenges to benefit Amazon customers and Sellers by optimizing business decision-making. This includes determining whether prices are set optimally according to measured customer demand and business objectives (Optimization), guaranteeing that promotions are incremental, using forecasting to recommend and rank the highest quality promotions are influence their schedule, amount, and type (Incrementality), and ensure our best prices and promotions are discoverable (Traffic Shaping).