Applied Scientist

Job ID: 1308557 | Services LLC


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.

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 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.

We are looking for talented Applied Scientists who can help us take our products to the next level who has deep passion for building machine-learning solutions; ability to communicate data insights and scientific vision, and has a proven track record of execute complex projects.

As an Applied Scientist in Machine Learning, you will:
· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines
· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production
· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management
· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation
· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
· Help attract and recruit technical talent


· 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
· M.S. or Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Applied Mathematics, or related discipline.
· Breadth and depth in knowledge and applications of machine learning algorithms and best practices.
· At least 5 years of hands-on experience in building Machine. Learning solutions to solve real-world problems.
· At least 3 years of experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.
· At least 3 years of experience with, at least, one modern programming language such as Java, Python, Scala, C++


· Ph.D. Degree in quantitative field with a strong Machine Learning background
· 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 or Storm/Samza
· Strong proficiency with Java, Python, Scala or C++
· 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 is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age