Applied Scientist, Sponsored Products, Amazon Ads

Key Skills

A/B Testing, Analytical and Problem solving, C++, NoSQL, Oracle, Python Programming, R Programming, RDBMS, SQL

Job Description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Why you love this opportunity

Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering 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 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 fundamentally 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.

Key job responsibilities

• Build machine learning models and utilize data analysis to deliver scalable solutions to business problems.
• Perform hands-on analysis and modeling with very large data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
• Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.
• Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.
• Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
• Research new predictive learning approaches for the sponsored products business.
• Write production code to bring models into production.

BASIC QUALIFICATIONS

• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Experience programming in Java, C++, Python or related language
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

PREFERRED QUALIFICATIONS

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.