Expires soon Amazon

Applied Scientist

  • San Francisco (City and County of San Francisco)
  • Community management

Job description


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 top 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:
· Use machine learning and data analysis to deliver scalable solutions to business problems
· 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, and perform statistical analysis
· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
· Research new machine learning approaches to all aspects of the sponsored products business

Ideal candidate profile


· M.S. or Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Applied Mathematics, or related discipline
· Breadth and depth knowledge of machine learning algorithms and best practices
· At least 3 years of hands-on experience in building Machine Learning solutions to solve real-world problems
· At least 2 years of experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
· At least 2 years of experience with, at least, one model programming language such as Java, Python, Scala, C++