AmazonPosted 1w ago

Applied Science Manager, Amazon Digital Advertising

Applied Science Manager, Amazon Digital Advertising at Amazon scores 86 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Seattleseniorfull-time$202k-$274k

AI in this role

computer-visionnlp

Lead a team of scientists who measure what matters—the real-world impact of Amazon’s marketing at billion-dollar scale. Amazon Advertising is one of Amazon’s fastest growing lines of business and our team occupies a unique position focused on maximizing the success of Amazon’s own marketing programs using our ad tech. Amazon marketing is Customer Zero for our ad tech, and our measurement science team is focused on quantifying the impact of the marketing that drives customers to discover and engage with Amazon’s products and services. We turn petabytes of retail, streaming, and customer signals into causal insights that make Amazon’s marketing spend smarter and more effective. As Customer Zero, we also extend the impact of methodologies, measurement systems, and insights we generate for Amazon’s marketing to directly inform the products and services we offer to external advertisers, shaping the tools that power the broader Amazon Ads ecosystem. This is a growth role for a successful candidate that is energized by building high-performing teams, tackling causal inference challenges that don’t have textbook answers, and shipping science that improves both Amazon’s own marketing and the advertising products used by the world’s largest brands.

Dozens of Amazon businesses use Amazon’s ad tech for their marketing objectives, driving more than $1B of marketing investments through Ads services and tools. As part of our team, this role will lead a cross-functional science team to measure the impact of Amazon’s marketing and identify opportunities for optimization at scale. You will set the strategic direction for your team, drive initiatives to make smarter marketing decisions, and improve the relevance of advertising to our customers. We move away from industry standard measurement systems and build sophisticated and insightful decision engines. We enable massive advertising programs, generating billions of impressions decorated with rich representations of customer state. The major challenges we are solving include integrating petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models. The successful candidate will have a strong technical background in ML and causal inference, experience with large scale data ML models, high judgment to drive business impact, an appreciation for white-space, and success building and developing high-performing teams.

Key job responsibilities
• Lead, hire, mentor, and develop a team of scientists and engineers, fostering a culture of innovation, scientific rigor, and operational excellence.
• Set the technical vision and roadmap for the team’s measurement and modeling initiatives, aligning with business priorities.
• Partner with senior leadership to define measurement strategies and translate business needs into science roadmaps and deliverables.
• Guide the team in applying ML, statistics, and econometrics to develop, analyze, and productionize prototype models.
• Drive the design and analysis of large-scale online experiments to validate models and measure impact.
• Foster collaboration across science teams through peer-review processes, publishing research internally and at industry conferences.
• Establish scalable, efficient, and automated processes for large-scale model development, validation, and implementation.

Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- 3+ years of scientists or machine learning engineers management experience
- 4+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience programming in Java, C++, Python or related language

Preferred qualifications

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- Domain expertise in quantitative marketing or advertising measurement.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 202,200.00 - 273,600.00 USD annually
USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionNlp

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer Vision and Nlp. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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