Sr. Applied Scientist, Customer Behavior Analytics (Marketing Measurement Solutions)
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $167,100 to $226,100
Employer-published annual base salary, USD. Advertised base range in Seattle, WA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSeattle, WA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (5 h ago) · observed since
About this job
Amazon’s Customer Behavior Analytics org is looking for an Applied Scientist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations.
A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will apply your expertise in ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.
Key job responsibilities
The main responsibilities for this position include:
- Apply your expertise in Transformer models, LLMs, ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions
- Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions
- Improve upon and simplify our existing solutions and frameworks
- Review and audit modeling processes and results from other scientists, both junior and senior
- Work with marketing leadership to align our measurement plan with business strategy
- Formalize assumptions about how our models are expected to behave and explain why they are reasonable
- Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making
- Develop and document scientific research to be shared with the greater science community at Amazon
About the team
The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.
Basic Qualifications
- 4+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- 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, WA, Seattle - 167,100.00 - 226,100.00 USD annually
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($167,100) is above 64% of the 329 Data & ML roles in Washington listed on this site; 32 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,000.
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 listingSr. Applied Scientist, Customer Behavior Analytics (Marketing Measurement Solutions)$167,100 to $226,100
Software Development Engineer, Neuron Collectives, Annapurna Labs$165,200 to $223,600
Software Development Engineer -Control Plane, AWS Scalable Intent Driven Routing (SIDR)$165,200 to $223,600
Software Engineer II - AI/ML, Neuron Inference, Neuron Inference$165,200 to $223,600
Software Dev Engineer II - AMZ27744.1$165,200 to $223,600
Machine Learning Engineer, FAI$165,200 to $223,600
Software Development Engineer, AI/ML, AWS Neuron, Model Inference$165,200 to $223,600
Chart as a table
| Role | Published base |
|---|---|
| Sr. Applied Scientist, Customer Behavior Analytics (Marketing Measurement Solutions) (this listing) | $167,100 - $226,100 |
| Software Development Engineer, Neuron Collectives, Annapurna Labs | $165,200 - $223,600 |
| Software Development Engineer -Control Plane, AWS Scalable Intent Driven Routing (SIDR) | $165,200 - $223,600 |
| Software Engineer II - AI/ML, Neuron Inference, Neuron Inference | $165,200 - $223,600 |
| Software Dev Engineer II - AMZ27744.1 | $165,200 - $223,600 |
| Machine Learning Engineer, FAI | $165,200 - $223,600 |
| Software Development Engineer, AI/ML, AWS Neuron, Model Inference | $165,200 - $223,600 |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-09-09
Where this pay comes from
Location as the employer wrote it: US, WA, Seattle
USA, WA, Seattle - 167,100.00 - 226,100.00 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.
