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DESCRIPTION

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. 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!

Basic qualifications:
* PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
* 3+ years of experience in 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.
* Technical leadership in machine learning.
* Effective verbal and written communication skills with non-technical and technical audiences.
* Experience working with 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.



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.



Key job responsibilities
As a Senior Applied Scientist on this team, you will:


* Be the technical leader in Machine Learning; lead efforts within this team and across other teams.
* 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.
* Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
* 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.