Applied Scientist , Sponsored Products

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
We are seeking an Applied Scientist to join our Supply Science team. This team is within the Sponsored Products team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant ads on the Amazon search page world-wide thereby enhancing the shopper experience. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference and data engineering.

Key job responsibilities
Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions of customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business.


As an Applied Scientist on this team you will:
* Drive end-to-end machine learning projects that have a high degree of ambiguity, scale and complexity
* Perform analysis on very large data sets to develop ideas and size opportunities; build machine learning models and conduct analysis to demonstrate potential business value
* Design A/B experiments, working with engineers to launch online experiments; conduct statistical analysis of the experimental results to derive understanding
* Build efficient and automated processes for large-scale feature generation, machine-learning model training, validation and serving. Work with engineers to productionize ML models.
* Develop new and innovative machine learning approaches, and collaborate with the science community.

A day in the life
The successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail and an ability to work in a fast-paced environment. Some examples of day-to-day activities include:
* Dive deep into the data to understand business opportunities and formulate the science problems
* Implement/create ML models to fit the observed data and predict customer response
* Conduct offline analysis to gauge business impact
* Communicate with PMs and engineers to discuss experiment plans and outcomes
* Work with engineers to conduct A/B tests or productionize your models.
* Collaborate with others scientists on problem solving and knowledge sharing.

About the team
We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon.

Basic Qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with neural deep learning methods and machine learning

Preferred Qualifications

- Experience in professional software development
- 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 - 172,400.00 - 223,400.00 USD annually
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually