Amazon Web Services-Senior Manager, Applied Science (Machine Learning)

San Francisco Bay Area, CA, United States; Palo Alto, CA, United Staets

About the job:

Amazon’s Advertising technology teams build the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. Our infrastructure supports millions of Internet users and handles billions of queries per day, all delivered in milliseconds. Our data platform processes massive data sets to develop business intelligence and analytics that are critical for the efficiency and profitability of our advertising business.

The Sponsored Product Ads Response Prediction team builds advanced machine-learning models and scalable machine-learning infrastructure to help better match shoppers’ intent to advertisements, optimize advertisers’ ROI, and scale a program that is accretive to Amazon. We are seeking an Applied Science Manager who has a solid background in applied Machine Learning, deep passion for building data-driven products; ability to communicate data insights and scientific vision, and has a proven track record of leading both applied scientists and software engineers to execute complex projects and deliver business impacts.


As an Applied Science Senior Manager , you will:
· Lead a group of talented applied scientists and software engineers to deliver machine-learning and AI solutions to production.
· Advance team’s engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.
· Develop science and engineering roadmap, run Sprint/quarter and annual planning, and foster cross-team collaboration to execute complex projects.
· Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
· Hire and develop top talents, provide technical and career development guidance to both scientists and engineers in the organization.

Impact and Career Growth:
· You will invent new shopper and advertiser experiences, and accelerate the pace of Machine Learning and Optimization.
· Influence customer facing shopping experiences to helping suppliers grow their retail business and the auction dynamics that leverage native advertising, this role will be powering the engine of one the fastest growing businesses at Amazon.
· Define a long-term science vision for our ad marketplace, driven fundamentally from the needs of our customers, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams.
· This is a role that combines science leadership, organizational ability, technical strength, product focus and business understanding.
· In the immediate term, this role requires (a) addressing principles of allocation function and pricing in ad marketplace auctions, (b) developing efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace auctions and to evolve them, and (c) develop science talent around machine learning, Economics and optimization for WW Advertising.

Why you love this opportunity:
· Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales.
· Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.
· We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.



· Ph.D in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Mathematics, or related discipline
· At least 7 years of experience in managing a team of Applied Scientists and Software Development Engineers.
· At least 7 years of experience in building large-scale machine learning and solutions at internet scale.
· At least 5 years of programming experience in Java, Python, Scala, C++, or other mainstream languages
· At least 5 years’ of experience in Big Data technologies such as: AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza.


· Experience with Internet-scale distributed technologies and concepts such as large-scale recommendation, personalization, search, advertising, etc.
· Published research work in academic conferences or industry circles
· Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization
· Experience in computational advertising