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Manager of Applied Science

Company:, Inc.
Location: Palo Alto
Posted on: May 3, 2021

Job Description:

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The 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 are seeking an experienced Applied Science Manager to join the Advertising Forecasting and Pricing team at Palo Alto, California. This team works on time series forecasting, auction theory, bid & allocation optimization, for Amazon Advertising business. Our group consists of talented scientists and engineers who owns our product end-to-end, from data collection, analysis, ideation, and prototyping, to development, metrics and monitoring. Our models and services are integrated directly with Amazon's Ad eco system, and our forecasts are used to drive key business decisions at the VP/SVP level. The scientists on the team also contribute to the larger science communities, publishing papers at conferences both internally and externally. We are a fast-growing team in a rapid paced Advertising business, doubling in size every year for the past five years.

AS an Applied Science Manager, you will:

  • Drive, build, and deliver the next generation of customer-facing machine learning solutions.
  • Bring a technical and scientific vision and leadership to Amazon's Ad Forecasting team and ensure that our product is unparalleled in terms of quality, capability, innovation, and customer experience.
  • Lead your team to deliver state-of-the-art Machine Learning (ML) based solutions to improve Amazon's Advertising performance and efficiency.

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.

  • PhD degree with 4+ years of applied research experience or a Master's 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
  • 3+ years of experience directly managing scientists and/or machine learning engineers
  • At least 5 years of experience in managing a team of applied scientists and engineers
  • At least 5 years of experience in building large-scale machine learning and AI solutions at scale.
  • Expertise in ML modeling and experience with the latest algorithms.
  • At least 2 years programming experience in Java, Python, Scala, C++, or other mainstream language
  • Proven track record of managing science teams, hiring and developing science talent
  • PhD in Computer Science, Applied Mathematics, Statistics or a closely related 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 and crisp verbal and written communication skills with non-technical and technical audiences.
  • Experience working with very large real-world data sets and building scalable models from big data.
  • Demonstrated successful industrial experience, drives results.
  • Thinks strategically, but stays on top of tactical execution.
  • Exhibits excellent business judgment; balances business, product, and technology very well.
  • Relentlessly high standards.
  • Dives deep think big and has convictions.

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

Keywords:, Inc., Palo Alto , Manager of Applied Science, Other , Palo Alto, California

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