Data Scientist, Amazon Ads Marketing Decision Science
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $153,400 to $207,500
Employer-published annual base salary, USD. Advertised base range in New York, NY
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationNew York, NY
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
About this job
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.
Basic Qualifications
- 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
Preferred Qualifications
- 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
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($153,400) is above 29% of the 462 Data & ML roles in New York listed on this site. Their median floor is $175,300; the middle half runs from $150,000 to $200,000.
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 7, 2026.
This listingData Scientist, Amazon Ads Marketing Decision Science$153,400 to $207,500
Senior Windows Client Engineer, Region Services Corporate Infrastructure (RSCI) - VECTOR Team$155K to $210K
Amazon Dedicated Cloud Engineer, US ADC Security$155K to $210K
Sr. Creative Manager, Brand Creative$155,100 to $209,800
Principal Business Intelligence Engineer, Amazon Customer Service$155,100 to $209,800
Technical Program Manager III - AMZ26509.1$154,785 to $201,200
Principal HRBP, AWS HR$154,700 to $209,300
Chart as a table
| Role | Published base |
|---|---|
| Data Scientist, Amazon Ads Marketing Decision Science (this listing) | $153,400 - $207,500 |
| Senior Windows Client Engineer, Region Services Corporate Infrastructure (RSCI) - VECTOR Team | $155K - $210K |
| Amazon Dedicated Cloud Engineer, US ADC Security | $155K - $210K |
| Sr. Creative Manager, Brand Creative | $155,100 - $209,800 |
| Principal Business Intelligence Engineer, Amazon Customer Service | $155,100 - $209,800 |
| Technical Program Manager III - AMZ26509.1 | $154,785 - $201,200 |
| Principal HRBP, AWS HR | $154,700 - $209,300 |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-10-26
Where this pay comes from
Location as the employer wrote it: US, NY, New York
USA, NY, New York - 153,400.00 - 207,500.00 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.
