Manager of Machine Learning Applied Science
- Palo Alto, CA
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.
As a hands-on Manager of Applied Science, you will
• Lead Science and Machine Learning for Amazon's Search Allocation team; tackle and drive challenging science and business problems that requires a balance between the interests of advertisers, shoppers, and Amazon.
• Create, Develop, and drive a data-driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities.
• Own a portfolio of pragmatic and long-term investments to drive long term growth of the ads and retail businesses.
• Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
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.
Team video ~ https://youtu.be/zD_6Lzw8raE
• M.S. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Mathematics, or related discipline
• At least 5 years of experience in managing a team of applied scientists and engineers.
• At least 5 years experience in building large-scale machine learning and AI solutions at scale.
• At least 5 years programming experience in Java, Python, Scala, C++, or other mainstream language
• Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Mathematics, or related discipline
• 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
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