Applied Scientist - Machine Learning - Advertising

Seattle, Washington, USA

Full Time
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Posted 2 weeks ago

Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. 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.

Sponsored Products helps merchants, retail vendors, and brand owners succeed via native advertising that grows incremental sales of their products sold through Amazon. The Sponsored Products Ad Marketplace organization optimizes the systems and ad placements to match advertiser demand with publisher supply using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with products - with a high relevance bar and strict latency constraints. Our goals are to help buyers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and to build a major, sustainable business that helps Amazon continuously innovate on behalf of all customers.

As an Applied Scientist for the Sponsored Products Detail Page Allocation and Pricing team, you will own systems which make the final decision on which ads to show, where to place them on the page and how many ads to place. This also includes selection of various themes that would appear in detail pages. This is a challenging technical and business problem, which requires us to balance the interests of advertisers, shoppers, and Amazon. You'll develop a data-driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities. You'll balance a portfolio of pragmatic and long-term investments to drive long term growth of the ads and retail businesses. You'll develop real-time algorithms to allocate billions of ads per day in advertising auctions.

Job Responsibilities:
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· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines.
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· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.
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· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management.
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· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
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· Research, design, and develop new machine learning approaches to drive continued scientific innovation.


Impact and Career Growth:
In this role you will have significant impact on this team as well as drive cross team projects that consist of Applied Scientists, Data Scientists, Economists, and Software Development Engineers. This is a highly visible role that will help take our products to the next level. You will work alongside many of the best and brightest science and engineering talent and the work you deliver will have a direct impact on customers and revenue!

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.

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
· Breadth and depth in machine learning, both from a theoretical and real-world applications perspective.
· Experience productionizing machine learning models.

Preferred Qualifications

· Experience in building large-scale machine-learning models for online recommendation, ads ranking, personalization, or search, etc.
· Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR, etc.
· Experience in computational advertising technology is a big plus
· 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.

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.


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Job tags: AWS Big Data Data Analytics Engineering Hadoop Java Machine Learning ML Python Research Spark
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