Sr Manager, PMT, Decision Science - Devices

We are seeking an experienced a Sr. Manager, Product Manager (Technical) to own the product strategy and roadmap for quantitative analysis products within Decision Science.

This leader will serve as the critical bridge between science teams and business stakeholders, translating complex model outputs into actionable business strategies for key device portfolios. The ideal candidate is equally comfortable interrogating the internals of a machine learning model as they are presenting portfolio strategy recommendations to senior Device leadership.

This role requires a rare combination of scientific fluency, product management excellence, and business acumen. You will shape how Amazon Devices leverages quantitative science to make better, faster, and more impactful decisions - from pre-launch forecasting to portfolio optimization.

Key job responsibilities

In this role, you will:

• Define and own the long-term product vision, strategy, and roadmap for quantitative analysis products that support demand forecasting, portfolio construction, and device economics;
• Lead, develop, and manage a team of data scientists and product managers, setting clear goals, providing technical mentorship, conducting performance reviews, and fostering a culture of scientific rigor, ownership, and cross-functional collaboration;
• Shape strategy for device portfolios by translating science-driven insights into actionable recommendations for product leadership;
• Identify high-impact opportunities where quantitative methods can displace or augment judgment-based decision-making
• Partner deeply with science teams to understand, evaluate, and challenge model methodologies, assumptions, and outputs - including econometric models, machine learning forecasts, conjoint analyses, and causal inference techniques
• Dive deep into science model outputs to validate accuracy, identify edge cases, and ensure business applicability; and,
• Translate complex quantitative concepts into clear, compelling narratives for non-technical stakeholders.
• Conduct leadership reviews to present science-backed portfolio recommendations
• Build and maintain strong relationships with cross-functional partners including supply chain, finance, marketing, and hardware engineering teams.
• Establish mechanisms to measure the business impact of science-driven decisions and continuously improve model adoption and trust.

About the team

The Decision Science team replaces judgment-based decisions with science-driven forecasts and quantitative analysis. We partner with engineers, scientists, and product managers to apply advanced science to forecast demand and efficiently allocate Amazon Device products across the portfolio.

We build and operate econometric and machine learning models that power lifetime demand forecasting, rapid reforecasting, mix adjustments, and portfolio optimization for product launches spanning eReaders, Tablets, Fire TV, Ring, Blink, and Alexa+-enabled devices.