Six Figure Work

Senior Applied Scientist, Ad Measurements Science

Amazon

Company websiteamazon.com (Amazon, opens in new tab)

Base salary $183,800  to $248,700

Employer-published annual base salary, USD. Advertised base range in New York, NY

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  • LocationNew York, NY
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (2 h ago) · observed since

About this job

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 a Senior Applied Scientist on the team, you will be at the forefront of innovation, developing measurement solutions end-to-end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics.

Key job responsibilities

  • Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies.
  • Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions.
  • Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models that measure the impact of ad spend across multiple platforms and timescales.
  • Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization.
  • Translate complex scientific challenges into clear and impactful solutions for business stakeholders.
  • Mentor and guide junior scientists, fostering a collaborative and high-performing team culture.
  • Foster collaborations between scientists to move faster, with broader impact.
  • Regularly engage with the broader scientific community with presentations, publications, and patents.

A day in the life

You will solve real-world problems by getting and analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication.

Team video https://advertising.amazon.com/help/G4LNN5YWHP6SM9TJ

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.

Basic Qualifications

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Knowledge of programming languages such as C/C++, Python, Java or Perl
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Preferred Qualifications

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

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 - 183,800.00 - 248,700.00 USD annually

Source: Amazon · View original posting (opens in new tab)

Pay in context

This role's base floor ($183,800) is above 64% of the 612 Data & ML roles in New York listed on this site; 13 others list the same floor. Their median floor is $170,000; the middle half runs from $140,000 to $197,300.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 6 other live Amazon roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Amazon roles with the nearest advertised base floor
RolePublished base
Senior Applied Scientist, Ad Measurements Science (this listing)$183,800 - $248,700
Software Development Manager, Volume Metadata, EBS$184,900 - $250,200
Sr. Robotics Software Engineer, Fauna$184,900 - $250,200
Software Development Manager, Off-Amazon Selection$184,900 - $250,200
Software Development Manager, AWS Proactive Security / AWS Piezo, AWS Proactive Security - AWS Piezo$184,900 - $250,200
Sr. SDE, Agentic Systems, Technical Content Experience (TCX) Engineering$184,900 - $250,200
Software Development Manager, AWS Quick$184,900 - $250,200

Same $100K to $400K scale as every card. All Amazon roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-06-02
Where this pay comes from

Location as the employer wrote it: US, NY, New York

USA, NY, New York - 183,800.00 - 248,700.00 USD annually

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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