Amazon Stores Ads Science team is looking for a Senior Applied Scientist to help translate state-of-the-art causal inference and machine learning research into production solutions. The individual will have the opportunity to shape the technical and strategic vision of a highly ambiguous problem space at the intersection of Amazon’s Stores and Advertising businesses, and deliver measurable business impacts via cross-team and cross-functional collaboration.

Amazon is investing heavily in building a world-class advertising business. Our advertising products are strategically important to Amazon’s Retail and Marketplace businesses for driving the long-term growth. The mission of the Stores Ads Science team is to identify opportunities to jointly optimize Amazon’s Stores and Advertising business, by enhancing the usage of advertising signals in Stores’ decision-making and vice versa to drive the long-term economic value to shoppers, sellers/vendors, and Amazon. Some of our work include measuring ads impact and shopping content incrementality to improve shopper experience, developing the science of explaining seller/vendor inter-related decisions between Stores and Ads (e.g.: pricing, Sponsored Ads participation) to optimize fees and incentives, and making Stores’ traffic acquisition strategies aware of shoppers’ and advertisers’ onsite advertising behavior.

We partner closely with tech and product teams across Stores and Advertising, and are constantly advancing experimentation methodology to accelerate science development and quantify business impacts. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action.

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, WA, Seattle - 167,100.00 - 226,100.00 USD annually