Sr. Applied Scientist , Amazon Ads

Amazon Ads is one of the fastest-growing businesses at Amazon, helping millions of advertisers — from first-time sellers to global agencies — reach customers at every stage of the shopping journey. Advertising Services' vision is that Amazon Ads is the ultimate partner for advertising customers. We deliver on this vision by building the internal tooling, automations, and platforms that enable efficient service delivery at scale — ensuring every advertiser, regardless of size or sophistication, has access to world-class support.

Are you excited about applying AI and machine learning to transform how a massive services organization operates? The Ad Services Engineering team builds and operates the systems that underpin the full spectrum of advertiser services — from self-service support experiences (Help content, Contact Us traffic patterns, knowledge bases) to managed campaign operations. We're investing in applied science to fundamentally change how advertisers get help, how campaigns get launched, how service teams find answers, and how we detect and resolve operational issues at scale. On the self-service side, we study patterns in Contact Us traffic, experiment with improving Help content effectiveness, and optimize the knowledge systems that power advertiser self-resolution. On the managed services side, we're building autonomous agents that handle low- and medium-judgment tasks currently performed by humans — freeing up Amazonians to focus on higher-value, strategic work. Across both, we're developing intelligent assistants and pioneering automated identification of product gaps from unstructured operational data — turning thousands of data points into actionable insights that drive product improvements.

As a Sr. Applied Scientist, you will be the science leader for AI-powered automation and intelligence within Advertising Services. You'll own the research and development of the machine learning systems that improve self-service advertiser experiences, power autonomous workflow agents, and drive operational intelligence — directly translating into higher self-service resolution rates, productivity gains measured in tens of thousands of hours annually, and measurable improvements in advertiser experience.

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
• - 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
• USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually