Applied Scientist, DSP Ranking Science

Job summary
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Machine Learning Optimization (MLO) team develops algorithms and systems that improve the performance and delivery of Amazon’s Display Advertising campaigns and automates campaign management using machine learning techniques. The team develops and deploys machine learning solutions that drive ad selection, bidding, user response prediction, and automated campaign management. Customers are advertisers and publishers who do business with Amazon.We own the system for batch training of user response prediction models, while the ad serving engineering team owns the real-time model scoring component. This teams owns the system for automated management of advertising campaigns, which can dynamically adjust parameters such as budget, bid prices, and targeting to optimize for campaign performance.

As an Applied Scientist on this team, you will:

• Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
• Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Run A/B experiments, gather data, and perform statistical analysis.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
• Research new and innovative machine learning approaches.
• Recruit Applied Scientists to the team and provide mentorship.

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

• Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
• Published research work in academic conferences or industry circles.
• Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
• Effective verbal and written communication skills with non-technical and technical audiences.
• Experience working with large real-world data sets and building scalable models from big data.
• Thinks strategically, but stays on top of tactical execution.
• Exhibits excellent business judgment; balances business, product, and technology very well.
• Experience in computational advertising.

Key job responsibilities
You will work on the next generation of our real-time pricing systems. These systems are optimizing the price of every individual opportunity on behalf of Amazon Advertising advertisers.

A day in the life

• Conduct offline analysis of data to guide design decisions with the product team
• Conduct A/B test setup and analyze results to guide rollout, go to market or development priority decisions
• Suggest and implement models to sophisticate the advertising products we offer to our customers

About the team
The Ranking team is responsible for real-time pricing decisions on the Amazon RTB (Real-Time Bidding) system

Basic Qualifications

• PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
• 2+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language

Preferred Qualifications

• Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
• Published research work in academic conferences or industry circles.
• Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
• Effective verbal and written communication skills with non-technical and technical audiences.
• Experience working with large real-world data sets and building scalable models from big data.
• Thinks strategically, but stays on top of tactical execution.
• Exhibits excellent business judgment; balances business, product, and technology very well.
• Experience in computational advertising.

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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.