Principal Data Scientist, AWS Analytics Engineering (AAE)

About the role

Do you want to define the multi-year science vision that transforms how millions of customers experience AWS products? Do you want to influence the AWS investment in Cloud and AI technology and see how your recommendations influencing AWS VP level decisions and driving the growth of AWS business? Do you want to push the boundaries of data science (e.g. statistical modeling, causal inference, econometrics, product growth analytics, and forecasting models) and democratize how AWS senior leaders access analytics insights using agentic analytics system?

The AWS Analytics Engineering is at the forefront of leveraging cutting-edge AI/ML technology and infrastructure to redefine how AWS product leaders and teams interact with and derive insights from their product and customer data. Our vision is to use data science methods to enable AWS product teams and business leaders to drive product and revenue growth and create personalized, optimized, and simplified product experiences to delight our customers.

We are looking for a customer-focused Principal Data Scientist to lead and define the science strategy across AWS services. In this role, you will set the technical direction for ML-driven product analytics across AWS Compute (EC2), GenAI & Agents, Database & Analytics, and Storage (S3) organizations. You will partner directly with GMs, VPs, and senior product leaders to translate complex business challenges into innovative scientific solutions that directly influence AWS's top line and bottom line. You will analyze underlying product growth insights, understand product growth drivers, and anticipate business risks that need to be surfaced to leadership.

As a Principal Data Scientist, you will be the technical thought leader who becomes a thought partner for senior leaders, hands on analyzing business trends and customer insights, drives cross-organizational decision alignment, and raises the bar for scientific rigor across the team. You will operate effectively in ambiguous environments, exercise strong business judgment on high-impact decisions, have high ownership and deep understanding of AWS business, and continuously push the frontier of data science applications at AWS scale.

Key job responsibilities

- Define and drive the multi-year science vision and data science roadmap for AWS product growth analytics across AWS Compute, Database & Analytics, Storage, AI/ML, and other organizations

- Attend AWS WBR to answer critical and timely business and analytics questions to drive clarify on AWS’ product growth strategy

- Influence senior leaders across multiple organizations by building mental models on AWS growth and anticipate growth risks that should be mitigated

- Serve as the technical thought leader and strategic advisor to senior AWS leaders (GM/VP level), translating business objectives into high-impact scientific decisions and identify opportunities that drives overall AWS product and revenue growth

- Establish best practices for decision science, including econometrics, statistical modeling, and causal methods