ML Scientist / Applied Scientist, Amazon

• PhD, or a Master's degree and experience in CS, CE, ML or related field
• 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
• If you're excited about advancing the state of the art in marketing science through innovative applications of ML, causal inference, and Bayesian statistics, while working on diverse problems that directly impact millions of customers, we want to hear from you

Desirable

• We're seeking an exceptional Applied Scientist to join our YouTube Marketing Science team, where you'll work on a broad spectrum of problems ranging from marketing measurement to algorithmic optimization
• Our solutions combine advanced ML, causal inference, and Bayesian modeling to drive marketing effectiveness at scale
• While you'll initially focus on building YouTube as Amazon's next variable marketing channel, you'll have opportunities to work across a broad spectrum of science problems. You'll tackle fascinating scientific and technical challenges like:
• Modeling customer dynamics and behavior changes over time
• Building recommender systems to nudge customers and increase engagement with products and offers
• Measuring marketing effectiveness across external channels (YouTube, TikTok, Google)
• Developing causal inference approaches to measure the impact of marketing actions
• Creating ML models for real-time bidding and campaign optimization
• Designing experimentation frameworks to understand marketing performance drivers
• Building GenAI systems to improve company productivity (our team is currently building a suit of GenAI products for analytics)
• Develop accurate and scalable machine learning models to address business use cases ranging from: modeling customer behavior, causal inferencing to model the value of customer incentivizes, recommender systems to increase customer engagement, or modeling and measurement marketing channels
• Lead and partner with engineering teams to drive modeling and technical design for complex business problems, often guiding engineers to apply the best scientific practices in software development
• Lead complex modeling analyses to help management and business stakeholders making key business decisions
• You'll join the PRIMAS (Prime & Marketing analytics and science) team, supporting the EU Prime and Marketing organization's science needs
• Our team works on a diverse portfolio of ML and science problems, currently including:
• Marketing measurement and optimization systems
• Customer behavior modeling
• Recommender systems for engagement
• Real-time bidding algorithms
• Causal inference frameworks
• Cross-channel marketing effectiveness
• Forecasting systems
• Ayesian statistics
• Tackle challenges across multiple scientific domain and use cases
• Develop novel approaches for ML & science, specially within marketing
• Build solutions that directly impact customer experience
• Collaborate with leading scientists across Amazon
• See your work drive business decisions
• Publish and present your research
• Build solutions that scale across global markets