Applied Scientist, Amazon Live Data Engineering, Sciences and Analytics (DESA)

Amazon Live is building the future of shoppable video connecting brands with customers through livestreams short-form video and creator-driven content across Amazon Shopping Fire TV Prime Video and social platforms. The product serves millions of monthly viewers processes billions of events daily across 9 marketplaces and generates tens of millions of dollars in advertiser revenue through self-service and managed channels with a goal to reach 100MM MAUs and 20K brands in the next couple of years. Amazon Live has a mature data platform powering reporting across 9 marketplaces 14 dashboards and real-time creator analytics. The opportunity ahead is different: proving the causal value of video to brands Amazons programmatic systems and product decision-making. This requires production ML models data experimentation frameworks and content intelligence that do not exist today and that is exactly what this role builds.

You will be one of the first scientists on this team defining the measurement methodology experimentation standards and model architecture from the ground up. The problems are high-ambiguity the data is rich and the impact is visible your models will directly influence how brands invest and how millions of customers discover content. Are you excited by the challenge of building causal measurement content intelligence and ranking signals from scratch for a product customers interact with daily Do you want to own the full lifecycle from research question through production deployment where your work moves multi-million dollar business decisions

We are looking for an Applied Scientist to join the DESA team and build production-grade models experiments and signals that close these gaps. You will own problems end-to-end from framing the research question through model deployment and A/B experimentation working alongside Data Engineers who build the infrastructure and a BIE who owns executive reporting. Your outputs will not sit in notebooks. They will run in production feed downstream ranking systems power brand-facing metrics and give partner teams the evidence they need to prioritize integrations with Amazon Live.

Key job responsibilities
- Design and deploy causal attribution models (incrementality testing multi-touch) replacing heuristic approaches producing defensible numbers for partner teams and brand-facing ROI metrics.
- Build brand lifecycle models (LTV cost-to-acquire adoption funnel) and campaign optimization models (marketing mix diminishing returns) that scale self-service revenue.
- Design and run A/B experiments with proper methodology (holdouts pre-registration power analysis) for new product surfaces ranking changes and attribution model transitions.
- Build multimodal and generative models for content intelligence extracting structured signals from video and producing scored creative assets at scale.
- Develop ranking and personalization features (content affinity creator quality indices cross-session engagement patterns) consumed by downstream distribution systems.
- Build predictive models proving video value to Amazons programmatic systems where existing retail signals fail.
- Own the full lifecycle from research question through production deployment monitoring and iteration.
- Present findings and methodology to senior leadership (Director/VP) and partner teams translating model outputs into business decisions.
- Contribute to the science community through internal publications reading groups and cross-team methodology sharing.
We value builders who thrive in ambiguity move fast from hypothesis to production and measure their success by business outcomes rather than paper count.

A day in the life
You will partner directly with product managers monetization leads and engineering peers to scope what to measure and how to prove it. Some weeks you will be designing an incrementality framework for ad lift and presenting methodology to leadership. Other weeks you will be training a multimodal model on broadcast video packaging ranking features for the distribution team or developing an A/B experiment for a new video produce on a new discovery surface. You will rapidly prototype and test hypotheses in a high-ambiguity environment making use of both quantitative analysis and business judgment. You will work on DE-built foundational data assets (content metadata shopper profiles retail/advertising integrations) and have access to a self-serve analytics agents and agentic-operational tooling that accelerate exploration. You will present findings to senior leadership (Director/VP level) and partner teams turning data into prioritization decisions.

About the team
The DESA team owns the data platform analytics and sciences for Amazon Live and Shop the Show. The teams mission: quantify the value of live video to Amazons ecosystem and make that value programmable for brands deciding where to invest for product teams deciding what to build and for Amazons systems deciding what to show customers. You will be one of the first scientists on a team that has built the data foundation and is now ready to build the intelligence layer on top.

The platform processes event data from internal Amazon systems and social surfaces across 9 marketplaces. DEs own the infrastructure and foundational data assets. The BIE owns executive reporting. Applied Scientists own the models experiments and signals that turn raw data into product value and business decisions. Your outputs become shared org infrastructure attribution models for partner teams ranking features for distribution experiment methodology for product and content intelligence for creative supply.

- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience working with PyTorch or JAX software or experience with Machine Learning and Large Language Model fundamentals including architecture training/inference lifecycles and optimization of model execution
- Experience with A/B testing especially around audience segmentation and targeting
- Experience with large scale distributed systems such as Hadoop Spark etc.
- Experience with causal inference methods (incrementality testing difference- in-differences instrumental variables or synthetic control).

- Experience in search advertising search marketing performance advertising or similar digital advertising
- Experience with video and image processing and compression algorithms and standards computer vision and/or machine learning
- Experience in a marketing focused role including customer lifecycle marketing segmentation reporting customer funnel analysis and top-line sales performance
- Experience working with cross-functional teams across business development marketing operations product development legal etc.
- Track record of deploying models that directly influenced product decisions or business strategy.
- Experience with Amazon internal tools (Bedrock SageMaker Redshift Cradle) is a plus but not required.

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 - 142800.00 - 193200.00 USD annually