Applied Scientist, Advertising Onsite Monetization

Arlington, Virginia, USA

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Job summary
*Candidates can be based in NYC, Seattle or Arlington Virginia (HQ2) *

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. 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!

Are you excited about advertising technology? Love to work at the intersection between machine learning, customer experience, and revenue growth? Are you interested in joining a diverse, fun, and quickly growing team (NYC, SEA, and Arlington HQ2) that offers opportunities in high growth businesses? Keep reading!

The Advertising Onsite Monetization Supply Science is leading innovation around how advertising is presented to shoppers across all Amazon owned properties. We maximize the long-term value that Amazon creates across its Display Advertising business by delivering an engaging ad experience for millions of shoppers each day. The team is inventing and testing new approaches to how advertising auctions work on the Amazon retail website worldwide, which involve bringing personalization to auction inputs and outputs and improving the core onsite auction mechanism. The team partners closely with both Retail and Advertising infrastructure teams and is responsible for optimizing billions of advertising auctions in over a dozen marketplaces.

We’re a new team that affords opportunity for immediate impact and long-term scope. We design algorithms and build services from scratch, while actively testing our ideas to demonstrate impact to the Ads business. The broader Advertising Onsite Monetization team looks to Supply Science to raise the bar for high quality, high velocity experimentation. Achieving our goals requires close collaboration between science and engineering. We’re looking for a leader to guide important technical decisions.

As an Applied Scientist on this team, you will:
  • Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
  • 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.
  • 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.

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.

Team video https://youtu.be/zD_6Lzw8raE

Basic Qualifications


  • PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
  • 2+ years of experience of 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.
  • Effective verbal and written communication skills with non-technical and technical audiences.
  • Experience working with large 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.


#omss
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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 https://www.amazon.jobs/en/disability/us.

Tags: A/B testing Big Data Computer Science Data analysis Economics Engineering Machine Learning Mathematics ML models PhD Python Research Statistics Testing

Perks/benefits: Career development Conferences

Region: North America
Country: United States
Job stats:  15  2  0
Category: Data Science Jobs

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