Principal Data Scientist, AWS Analytics Engineering; AAE

Description

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.

• 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 W  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
• Invent, operationalize, and scale novel analytical frameworks and metrics that enable data-driven product growth and executive decision-making
• Mentor junior decision scientists, setting the bar for technical quality through code reviews, design reviews, and hands‑on guidance
• Communicate findings, conclusions, and strategic recommendations to both technical and non-technical executive audiences through effective verbal and written communication
• Identify and champion new science opportunities that expand AAE’s impact across AWS, building the case for investment and driving adoption

As a Principal Data Scientist in AAE org, you will shape the science strategy that underpins product decisions across multiple AWS organizations. You'll spend your time partnering with VPs and GMs to identify the highest-leverage data science opportunities, architecting novel ML solutions to complex product challenges, and mentoring scientists across the team. You'll drive alignment across cross-functional stakeholders, ensure scientific rigor in our most critical initiatives, and communicate insights that directly influence AWS product roadmaps and growth strategy.

You'll balance long-term vision-setting with hands‑on technical leadership, diving deep into model architectures and data pipelines when needed.

We are a team of scientists and engineers supporting AWS product leaders to make high-impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We come from diverse backgrounds in statistics, computer science, engineering, and business analytics. We…