Data Scientist, Prime Video Sports

Description

Prime Video is one of the world's fastest-growing entertainment destinations, with Live Sports at the center of that growth. From NFL and NBA to Premier League and Champions League, Prime Video is becoming a premier home for live sports globally.

Our team owns the data science that shapes how tens of millions of customers discover and experience Sports content on Prime Video. We build measurement frameworks, experimentation systems, and analytical foundations powering Search, Recommendations, and the live broadcast experience itself.

Sports presents uniquely exciting challenges: content is live and time-sensitive, customer intent shifts rapidly, and the difference between a great and poor experience is measured in minutes. We tackle problems like real-time search intent during live matches, sports engagement and long-term retention, broadcast optimization for global audiences, and personalization across vastly different affinities, from die-hard fans to first-time viewers.

You'll work on large-scale experimentation, novel measurement methodologies, and data-driven decisions that directly shape the Prime Video customer experience. This is a ground-floor opportunity to define the data science practice for an expanding domain, from content discovery through the live viewing experience, partnering with Applied Scientists, Software Engineers, Product Managers, and Broadcasting Teams to turn insights into global product impact.

Key job responsibilities

• Experimentation at scale: Design, execute, and analyze A/B tests, from short-cycle learning experiments to full product launches across worldwide marketplaces
• Measurement & metrics: Build frameworks to measure content discovery quality, search recall, recommendation relevance, and broadcast experience, including novel methodologies for live, time-sensitive content
• Sports analytics: Deep-dive into customer behavior around live events: engagement patterns, affinity segmentation, broadcast quality, and tentpole event dynamics
• Product partnership: Partner with Applied Scientists, Engineers, and Product Managers to define requirements, evaluate models, and drive data-informed decisions
• Analytical leadership: Own data structures, metrics definitions, and best practices. Communicate findings clearly to technical and business stakeholders
• Shape a growing domain: Help define the data science roadmap as we expand into new areas of live sports
  
  

• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Bachelor's degree or above in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Experience in A/B testing
• Strong proficiency with SQL
  
  

• Experience in a ML or data scientist role with a large technology company
• Statistical modeling and causal inference methods
• Python for data analysis and machine learning
• Distributed data technologies (e.g., Redshift, SparkSQL, Athena)
• Familiarity with recommendation systems, search, or streaming
• Interest in sports and live entertainment