Amazon is hiring : Applied Scientist II, Advertising Incrementality Measurement i

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Description : Application deadline : Dec 17, 2025. The Advertising Incrementality Measurement (AIM) team is looking for an Applied Scientist II with experience in causal inference, experimentation, and ML development to help expand causal modeling solutions for understanding advertising effectiveness. Our work supports customer-facing experimentation tools, internal research & development, and Amazon's Multi-Touch Attribution (MTA) measurement offerings. Incrementality measurement is a key part of the next generation of Amazon Advertising measurement solutions, and this role will contribute to the release and expansion of these offerings.

Responsibilities

Partner with economists and senior team members to drive science improvements and implement state-of-the-art ML and econometrics solutions.

Collaborate with engineering and other science teams to design, implement, prototype, deploy, and maintain large-scale causal ML models.

Conduct in-depth research and analysis on advertising-related datasets, including large real-world experimental data, to understand advertiser behavior, identify model improvement opportunities, and assess limitations.

Define data quality standards for understanding typical behavior, capturing outliers, and detecting model performance issues.

Work with product stakeholders to improve measurement of advertising effectiveness for customers.

About The Team

AIM is a cross-disciplinary team of engineers, product managers, economists, data scientists, and applied scientists focused on scalable, scientifically-rigorous causal inference methodologies. Our work helps customers understand actions, behaviors, and strategies that have real, measurable impact on outcomes. The data we produce informs advertisers and partners making decisions involving high advertising spend.

Basic Qualifications

3+ years of building models for business applications.

PhD, or Master’s degree with 4+ years of CS, CE, ML, or related field experience.

Experience programming in Java, C++, Python, or related language.

Experience with ML toolkits such as sklearn, PyTorch, TensorFlow, etc.

Experience with data exploration and querying technologies such as pandas, SQL, and Spark.

Very strong written communication skills with the ability to distill complex technical details into tangible insights for leaders and stakeholders.

Preferred Qualifications

Experience with causal inference, A / B testing, and experimentation.

Experience with MLOps practices for developing models in production.

Experience with causal ML modeling (e.g., double machine learning, uplift modeling).

Familiarity with AWS systems (S3, EMR, SageMaker).

Experience with statistical visualization (ggplot2, Plotly, Seaborn).

Experience with digital advertising is a bonus, but not required.

Equal Opportunity

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application or hiring process, please visit the accommodations page for more information. If the country / region you’re applying in isn’t listed, please contact your Recruiting Partner.

Compensation

Our compensation reflects the cost of labor across several US geographic markets. Colorado base pay ranges from $142,800 / year to $193,200 / year; national base pay ranges from $136,000 / year to $223,400 / year. Pay is based on location, knowledge, skills, and experience. Depending on the position, equity, sign-on bonuses, and other benefits may be provided as part of a total compensation package. For more information, please visit the Amazon benefits page. This position will remain posted until filled. Applicants should apply via our internal or external career site.

Company

Amazon.com Services LLC

Job ID : A2906519

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