Senior Applied Science Manager, AWS Analytics Engineering (AAE)

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 GenAI technology and see the impact of your leadership moving the needle on billions of dollars of AWS business Do you want to lead cross functional team that impacts multiple organizations (product sales marketing finance) in AWS Do you want to push the boundaries of AI/ML technology (e.g. multi-agent analytics system agentic knowledge representation and management graph neural networks reinforcement learning causal inference optimization and LLM-based forecasting models) to build scalable ML products that help AWS grow and delight our customers

The AWS Analytics Engineering (AAE) 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 data. We are a cross functional org from decision science ML products data platform and agentic analytics system. Our vision is to use artificial intelligence and machine learning to enable AWS product teams product and go to market leaders to drive product growth and create personalized optimized and simplified product experiences to delight our customers. We shape AWS product features (e.g. Console Spot and Autoscaling) influence GTM efficiencies with customer propensity models democratize data and insights access through multi-agent system and influence AWS leaders product strategy.

We are looking for a customer-focused solutions-oriented Senior Applied Science Manager to lead and define the science and engineering strategy across AWS product this role you will set the technical direction for agentic analytics products build ML features for AWS products to optimize their operations influence product growth related decision science for senior leaders generate ML-driven sales leads for AWS GTM teams innovate multi-agent analytics system develop big data engineering system at the AWS data scale. You will partner directly with GMs VPs and senior product leaders from major AWS product management marketing and sales organization to translate complex business challenges into innovative scientific solutions that directly influence AWSs top line and bottom line.

As a Senior Applied Science Manager you will be the technical thought leader who establishes the science roadmap analytics software development drives cross-organizational alignment and raises the bar for scientific rigor across the team. You will work cross organization from AWS product management engineering sales marketing and finance. You will operate effectively in ambiguous environments exercise strong business judgment on high-impact decisions drive the innovation and publication roadmap and continuously push the frontier of whats possible with ML-driven product intelligence at AWS scale.


Key job responsibilities
Define and drive the multi-year science ML product and software engineering vision and roadmap for ML-powered product analytics across AWS Products Marketing and Sales organization
- Build lead and develop a high-performing team of technical managers applied scientists and software engineers including hiring top talent managing performance and growing careers through mentorship and promotion readiness
- Partner with senior AWS leaders (GM/VP level) to identify strategic data-driven opportunities and translate business objectives into high-impact scientific initiatives
- Architect and guide enterprise-scale ML and agentic platform including agentic system knowledge representation big data platform deep learning graph neural networks reinforcement learning causal inference and forecasting models that predict business outcomes and enhance customer experiences
- Manage cross-functional science and software engineering team to build ML driven products that are scalable and leading industry best practices at the AWS scale and speed
- Invent operationalize and scale novel analytical frameworks and metrics that enable data-driven product growth and executive decision-making
- Communicate findings conclusions and strategic recommendations to technical and non-technical business leaders across AWS
- Mentor scientists and engineers establish best practices for experiment design and model evaluation and review technical artifacts to ensure quality
- Identify and champion new science opportunities that expand AAEs impact across AWS building the case for investment and driving adoption


A day in the life
As a senior applied science manager in AAE org you will shape the science strategy that underpins product decisions across multiple AWS organizations. Youll spend your time partnering with VPs and GMs to identify the highest-leverage science opportunities architecting novel ML solutions to complex product challenges and mentoring scientists across the team. Youll drive alignment across cross-functional stakeholders ensure scientific rigor in our most critical initiatives and communicate insights that directly influence AWS product roadmaps. Youll balance long-term vision-setting with hands-on technical leadership diving deep into model architectures and data pipelines when needed while maintaining the strategic altitude to guide the teams direction. You will manage cross functional science and engineering team to build cutting edge agentic system and ML products that transform our product and customer experience.

About the team
We are a team of scientists and software 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 specialize in the full end-to-end ML development process including data ingestion ETL model development and model deployment in production. We provide AI/ML services across decision science ML products multi-agent analytics systems and data engineering platform.

High Impact Projects: We work on high-impact high-visibility projects that directly influence AWS product roadmaps and senior leaders decisions.
Supportive Team Environment: We are proud of our supportive and inclusive team culture we have each others back during ups and downs.
Work-Life Balance: We believe 80% of value comes from 20% of work so we always prioritize our backlog ruthlessly based on business value.
Learning Opportunity: Extensive opportunities to understand AWS business and leverage state-of-the-art AI/ML and cloud technology.


- 10 years of building large-scale machine learning and AI solutions at Internet scale experience
- Masters degree in Computer Science (Machine Learning AI Statistics or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

- 10 years of practical work applying ML to solve complex problems for large-scale applications experience
- 5 years of hands-on work in big data machine learning and predictive modeling experience
- 5 years of people management experience
- PhD in Computer Science (Machine Learning AI Statistics or equivalent)
- Experience in practical work applying ML to solve complex problems for large scale applications
- Experience working with big data machine learning and predictive modeling

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 218800.00 - 295900.00 USD annually