Data Scientist

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 experienced Data Scientist to join the Sponsored Products Auction team. This team is responsible for building and evaluating mechanisms to rank and price billions of ad impressions per day. We're looking for a Data Scientist to define measures of auction efficiency and produce insights into the quality of inputs to our auction (supply, demand, ML model predictions). This role will also be responsible for exploratory data analysis to identify opportunities for improvement of the system and working closely with Economists, Applied Scientists and Engineers to improve our product.

As a Data Scientist on this team, you will:
- Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.
- Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
- Apply statistical and machine learning knowledge to specific business problems and data.
- Build decision-making models and propose solution for the business problem you define.
- Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
- Analyze historical data to identify trends and support optimal decision making.
- Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.

Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.

Team video https://youtu.be/zD_6Lzw8raE