Applied Scientist, Ads Measurement Science

Amazon•New York, NY

15d

About The Position

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high-effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers.

Requirements

2+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience building machine learning models or developing algorithms for business application

Nice To Haves

Experience with popular deep learning frameworks such as MxNet and Tensor Flow
Experience in professional software development
Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
Experience in designing experiments and statistical analysis of results
Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Experience in patents or publications at top-tier peer-reviewed conferences or journals

Responsibilities

Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems
Disambiguate problems to propose clear evaluation frameworks and success criteria
Work autonomously and write high quality technical documents
Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production
Partner closely with other scientists to deliver large, multi-faceted technical projects
Share and publish works with the broader scientific community through meetings and conferences
Communicate clearly to both technical and non-technical audiences
Contribute new ideas that shape the direction of the team's work
Mentor more junior scientists and participate in the hiring process