Applied Science Manager, Sponsored Products and Brands -- Offsite

Amazon is a leading technology company re-imagining the advertising landscape through generative AI technologies. The Applied Science Manager will lead a team of scientists and engineers to develop machine learning and AI solutions that enhance advertising outcomes and shape product direction.

Responsibilities:

• Lead Applied Scientists, Machine Learning Engineers, and Software Development Engineers
• Surface qualitative and quantitative insights as the voice of the advertisers to shape product direction and ensure product-market fit
• Develop science and engineering roadmaps to increase advertiser outcomes with ML and GenAI solutions, run annual planning, and foster cross-team collaboration on model development
• Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization
• Stay informed about recent scientific publications, industry trends, and system designs
• Work with off-Amazon publishers to launch new high-impact placements that increase advertiser outcomes
• Develop and own mechanisms to track and improve advertiser performance
• Distill complex ideas complex thoughts, succinctly, adapting to the medium of communication

Requirements:

• 4+ years of applied research experience
• 3+ years of scientists or machine learning engineers management experience
• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Knowledge of ML, NLP, Information Retrieval and Analytics
• Experience programming in Java, C++, Python or related language
• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
• Experience in practical work applying ML to solve complex problems for large scale applications
• Experience working with big data, machine learning and predictive modeling
• Experience in people management
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc