Applied Scientist , AWS Marketing Science

As an Applied Scientist II specializing in lead scoring and deep learning modeling you will build and improve machine learning models that power how our business engages with customers. You will develop predictive models for customer segmentation scoring and lead/account prioritization working within an established scoring architecture and collaborating with senior scientists and cross-functional teams to deliver production-grade components.

Key job responsibilities
* Build and iterate on predictive lead scoring models to support customer acquisition conversion and retention strategies using techniques such as survival analysis graph networks or transformer-based architectures.

* Develop and maintain ML pipeline components for deep learning models including data preprocessing feature engineering model training and inference integration.

* Contribute to internal and external research including science reviews technical publications and patent filings in collaboration with senior scientists.

* Apply multi-modal modeling techniques (text graph behavioral and temporal data) to enhance scoring accuracy across account and lead levels.

* Conduct A/B testing causal inference and counterfactual analysis to measure model impact and iterate on model design.

* Partner with MLOps engineers on model deployment monitoring and retraining using tools like AWS SageMaker MLflow and other internal tools.

* Participate in science reviews to maintain and raise the quality bar within the team.

* Implement and execute offline and online evaluation frameworks; track success metrics tied to business outcomes (conversion rates pipeline generation).

About the team
The AWS Marketing Science team builds the ML models and measurement systems that drive marketing decisions across Amazon Web Services. We own incrementality and valuation ROI measurement marketing attribution propensity scoring account and lead clustering and next-best-action models. Our work directly influences how AWS allocates marketing spend targets accounts and measures effectiveness across billions in pipeline.

- 2 years of building models for business application experience
- PhD or Masters degree and 2 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience in professional software development

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 NY New York - 172400.00 - 223400.00 USD annually
USA TX Austin - 142800.00 - 193200.00 USD annually
USA VA Arlington - 142800.00 - 193200.00 USD annually
USA WA Seattle - 142800.00 - 193200.00 USD annually