Principal Applied Scientist, Ads Measurement Science

Amazon; New York (NY); On-site; USD 260,000 - 380,000; Full time

Job summary

Amazon Ads' Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) organization seeks a Principal Applied Scientist to lead the technical vision and execution for performance measurement across our advertising products. We tackle holistic impact, privacy-aware measurement, and scalable modeling across online/offline channels.

You will guide a team of scientists across ML, NLP, CV, causal inference, and generative AI, shaping roadmaps and driving production-ready research.

Responsibilities

• Driving the scientific vision of the teams in your organization and you advise and influence its technical leadership on performance measurement models and products.
• Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems. You solve problems pragmatically, applying judgment and experience to balance trade-offs between competing interests.
• Bringing clarity to complex problems, probing assumptions, illuminating pitfalls, fostering shared understanding, and guiding towards effective solutions.
• Serving and being recognized by internal and external peers as a thought leader in modeled measurement in Ads. You will engage routinely with the broader scientific community, e.g. as a reviewer, program committee member, workshop organizer, or chair at peer-reviewed internal/external conferences.
• Leading by example, with your papers, analyses, and code setting the standard in your organization for scientific engineering excellence.
• Leading science and design reviews, aligning teams across your organization around coherent algorithmic strategies.
• Influencing your team’s science and business strategy by driving one or more team roadmaps contributing to the organization’s roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch.
• Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices. You drive the documentation of scientific innovation. You attract bar-raising talent from academia and industry.
• Staying abreast of academic and industry trends, knowing the state of the art, and building on top of existing solutions instead of reinventing when possible.

Job description

Description

The Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) organization 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.

This Principal Applied Scientist leads the technical vision and execution for Amazon Advertising's performance measurement. Our measurement products and tools help customers understand the holistic impact of their spend on Amazon Ads and optimize their portfolios. This is a complex, multi-disciplinary scientific space spanning machine learning, causal inference, statistics and experimentation, natural language processing, and generative AI. As a GenAI-first organization, we build foundational and agentic models that power advertiser use cases across Ads, while empowering our Applied Scientists to directly build and ship products.

You will guide a team of scientists with expertise across different domains to come together and innovate on some of the hardest problems in advertising, made more challenging by evolving privacy regulations and technological changes. In measuring the comprehensive impact of advertising, key challenges you will tackle include capturing impact: 1) both for identified and increasingly unidentified web traffic in light of an evolving global privacy landscape; 2) for outcomes across retailers, including both within and beyond Amazon; and 3) for both short- and long-term impacts of advertising.

Key job responsibilities

• Driving the scientific vision of the teams in your organization and you advise and influence its technical leadership on performance measurement models and products.
• Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems. You solve problems pragmatically, applying judgment and experience to balance trade-offs between competing interests.
• Bringing clarity to complex problems, probing assumptions, illuminating pitfalls, fostering shared understanding, and guiding towards effective solutions.
• Serving and being recognized by internal and external peers as a thought leader in modeled measurement in Ads. You will engage routinely with the broader scientific community, e.g. as a reviewer, program committee member, workshop organizer, or chair at peer-reviewed internal/external conferences.
• Leading by example, with your papers, analyses, and code setting the standard in your organization for scientific engineering excellence.
• Leading science and design reviews, aligning teams across your organization around coherent algorithmic strategies.
• Influencing your team’s science and business strategy by driving one or more team roadmaps contributing to the organization’s roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch.
• Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices. You drive the documentation of scientific innovation. You attract bar-raising talent from academia and industry.
• Staying abreast of academic and industry trends, knowing the state of the art, and building on top of existing solutions instead of reinventing when possible.

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.