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 their 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 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.
For this role, we are seeking a talented scientist with deep expertise in Gen AI to innovate our product portfolio and ease accessibility to actionable insights for our customers.
Key job 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
About the team
We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
Team Video: https://youtu.be/zD_6Lzw8raE- 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- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
