Amazon Advertising LLC
Posted Oct 25, 2026
Data Scientist, Amazon Ads Marketing Decision Science
Midtown · Onsite · Mid · $153.4K–$207.5K
Help moving to NYC
Visa sponsorship likely
Based on 5 NYC H-1B filings for related roles (Data Engineer III, Data Engineer II) at Amazon Advertising LLC, Oct 2025–Jun 2026. This is historical evidence, not a promise of sponsorship.
Relocation assistance not stated
Relocation assistance is not stated in this posting.
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Pay
Posted$153,400–$207,500 / year
USA, NY, New York - 153,400.00 - 207,500.00 USD annually
H-1B record$158K Company-wide NYC H-1B median offered wage at Amazon Advertising LLC: $158,100 (56 filings, Oct 2025–Jun 2026). Not specific to this role.
About the role
Amazon Advertising drives billions of ad impressions and millions of clicks daily, powering discovery and sales for advertisers across Amazon's Retail and Marketplace businesses. The Ads Marketing Decision Science team sits at the intersection of data science and marketing strategy. We build intelligent, data-driven systems that analyze advertiser behavior at large scale to deliver the right guidance to the right advertiser at the right time. Our work spans behavioral modeling, content intelligence, automated decision systems, and GenAI applications, enabling personalized marketing experiences that help advertisers make smarter advertising decisions and grow their business on Amazon.
We are looking for a Data Scientist who brings strong fundamentals in machine learning, causal inference, and statistical modeling to solve real advertiser problems. You will build predictive models, design experiments, develop segmentation frameworks, and leverage GenAI capabilities where applicable, taking solutions end-to-end from proof-of-concept to production at scale. You will partner closely with scientists, engineers, and product managers on a daily basis to prototype rapidly, ensure data integrity in production systems, and deliver measurable advertiser impact. If you are passionate about solving real-world problems with cutting-edge science, come join us as we innovate and make history.
Key job responsibilities
• Define and execute data science solutions end-to-end, from problem framing through production deployment.
• Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations.
• Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions.
• Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making.
• Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale.
• Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions.
• Leverage GenAI and LLM capabilities to enhance science products where applicable
A day in the life
You will solve real-world problems by analyzing large volumes of advertiser data, building predictive models, designing experiments, and measuring business impact. You will prototype rapidly, validate ideas with data, and partner with engineers to productize and scale successful solutions. You will collaborate daily with scientists, engineers, and product managers across the advertising organization, working in a cross-functional, fast-paced environment where data drives decisions and helps advertisers grow.
About the team
We are a team of Applied Scientists, Research Scientists, Data Scientists, and Business Intelligence Engineers with deep expertise in ML, NLP, Gen-AI, RL, and causal inference, from a diverse range of backgrounds. We partner closely with strong engineers, product managers, and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
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.
USA, NY, New York - 153,400.00 - 207,500.00 USD annually
We are looking for a Data Scientist who brings strong fundamentals in machine learning, causal inference, and statistical modeling to solve real advertiser problems. You will build predictive models, design experiments, develop segmentation frameworks, and leverage GenAI capabilities where applicable, taking solutions end-to-end from proof-of-concept to production at scale. You will partner closely with scientists, engineers, and product managers on a daily basis to prototype rapidly, ensure data integrity in production systems, and deliver measurable advertiser impact. If you are passionate about solving real-world problems with cutting-edge science, come join us as we innovate and make history.
Key job responsibilities
• Define and execute data science solutions end-to-end, from problem framing through production deployment.
• Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations.
• Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions.
• Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making.
• Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale.
• Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions.
• Leverage GenAI and LLM capabilities to enhance science products where applicable
A day in the life
You will solve real-world problems by analyzing large volumes of advertiser data, building predictive models, designing experiments, and measuring business impact. You will prototype rapidly, validate ideas with data, and partner with engineers to productize and scale successful solutions. You will collaborate daily with scientists, engineers, and product managers across the advertising organization, working in a cross-functional, fast-paced environment where data drives decisions and helps advertisers grow.
About the team
We are a team of Applied Scientists, Research Scientists, Data Scientists, and Business Intelligence Engineers with deep expertise in ML, NLP, Gen-AI, RL, and causal inference, from a diverse range of backgrounds. We partner closely with strong engineers, product managers, and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
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 - 153,400.00 - 207,500.00 USD annually