Applied Scientist, Prime Video Science

We're looking for an Applied Scientist to join the Prime Video Science team, which leverages machine learning, AI, and causal inference to guide major entertainment decisions—what content to create, license, or invest in. Our models simulate global customer behavior to answer critical "what-if" questions, directly shaping business strategy and investment.

About the role

As an Applied Scientist, you will build large-scale machine learning and deep learning models on global data to simulate customer behavior. You’ll collaborate with business, finance, engineering, and science teams to take ideas from prototype to production. Strong communication skills and the ability to translate data-driven insights into actionable recommendations are essential. The ideal candidate thrives in ambiguity, pays close attention to detail, and works effectively in a fast-paced environment.

Responsibilities

• Build models that simulate customer behavior to answer counterfactual "what-if" questions, guiding content and product investment decisions.
• Apply deep learning, reinforcement learning, causal inference, and experimental design to large-scale customer data to model responses to change.
• Design and prototype agentic AI systems and other novel ML approaches, researching new methods to improve model accuracy and scalability.
• Validate and calibrate models against real-world randomized experiments, partnering with engineers to deliver scalable, production-ready systems.
• Translate model outputs into clear recommendations and communicate results to stakeholders through technical papers and business-facing documents.

About the team

The Prime Video Science team is a multidisciplinary group of applied scientists, data scientists, economists, and engineers. We tackle some of the most challenging research questions in the business, with visibility up to the CFO and CEO levels. Our work sits at the intersection of machine learning, AI, and causal inference, driving innovations that enhance customer experience and business profitability.

Requirements

• 3+ years of experience building machine learning models or developing algorithms for business applications.
• PhD, or Master’s degree and 4+ years of experience in CS, CE, ML, or a related field.
• Experience with patents or publications at top-tier peer-reviewed conferences or journals.
• Proficiency in programming languages such as Java, C++, or Python.

Preferred Qualifications

• Experience designing state-of-the-art deep learning models, including training, optimization, and model pruning.
• Experience investigating, designing, prototyping, and delivering innovative system solutions.
• Professional software development experience.
• Experience with reinforcement learning, agentic AI system design, and/or causal inference.

Pay

Base salary ranges:

• Culver City, CA: $142,800 – $193,200 USD annually
• Seattle, WA: $142,800 – $193,200 USD annually

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with optional supplemental life plans).
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.
• Sign-on payments and restricted stock units (RSUs).

Learn more about our benefits at amazon.jobs/en/benefits.