Advertising at Amazon is a fast-growing multi-billion dollar business that encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers, extending across US, EU and an increasing number of international geographies. Sponsored Ads is a native pay-per-click advertising program targeted at sellers and vendors seeking to market their products. The Traffic Quality team's charter is to identify robotic impressions and clicks in Sponsored Ads, and weed them out to ensure a high quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by implementing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that leverages Amazon's unique signals to ensure precise traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend.
We are looking for a dynamic, innovative and accomplished Senior Applied Science Manager to lead machine learning and data science for the Advertising Traffic Quality vertical. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? As an Applied Sciences Manager for Traffic Quality, you will lead a team of applied scientists, data scientists and engineers to deliver to conceptualize and build algorithms that efficiently detect and filter invalid traffic. You will be the single-threaded owner of the algorithms that go into our traffic quality systems and will be responsible for both near-term improvements to existing algorithms as well as long-term direction for Traffic Quality algorithms. Your team will include experts in machine learning, statistics and analytics that are working on state-of-the-art modeling techniques, as well as generating insights that fuel critical investments. You will also lead an engineering team that works on handling terabyte scale data and implementing features and algorithms that process billions of events per day. You will interface with product managers and operations teams to bring key advertising initiatives to customers. Your strong management skills will be utilized to help deliver critical projects that cut across organization structures and meet key business goals.
• Deliver key goals to enhance advertiser experience and deliver multi-million dollar savings by building algorithms to detect and mitigate invalid traffic
• Use machine learning and statistical techniques to create new, scalable solutions for invalid traffic filtering
• Drive core business analytics and data science explorations to inform key business decisions and algorithm roadmap
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Hire and develop top talent in machine learning and data science and accelerate the pace of innovation in the group
• Build a culture of innovation and long-term thinking, and showcase this via peer-reviewed publications and whitepapers
• Work with your engineering team and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
• Keep updated on the industry landscape in Traffic Quality and identify algorithm investments to achieve an industry leading traffic quality solution.
• Learn continuously about new developments in machine learning and AI, as well as recent innovations in creative intelligence and malware detection. Identify how these can be rolled into building an industry leading solution for Amazon advertising
• A MS in CS focused on Machine Learning, Statistics, Operational research or in a highly quantitative field
• 5+ years of hands-on experience in big data, machine learning and predictive modeling
• 5+ year people management and cross department functional experience
• Knowledge of a statistical analysis package such as R, Tableau, and high-level programming language (E.g. Python) used in the context of data analysis and statistical model building
• Strongly motivated by entrepreneurial projects and experienced in collaboratively working with a diverse team of engineers, analysts, and business management in achieving superior bottom line results
• Strong communication and data presentation skills
• Strong ability in problem solving and driving for results
• Technical leader with 12+ years of exceptional, hands-on experience in machine learning in e-commerce, fraud/risk assessment, or an enterprise software company building and providing analytics or risk management services and software.
• Ph.D. degree in in Statistics, CS, Machine Learning, Operations Research or in a highly quantitative field.
• Knowledge of distributed computing and experience with advanced machine learning libraries like Spark MLLib, Tensorflow, MxNet, etc.
• Strong publication record in international conferences on machine learning and artificial intelligence