Applied Scientist - Brand Shopping Experience

Job description

DESCRIPTION

Excited about the future of brand-centric advertising and shopping on Amazon? Want to bring the best, emerging, and trending brands to shoppers, while driving strong value to brands? 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.

Brand Advertising & Shopping Experience (BASE) org is looking for an Applied Scientist with experience in developing and productizing state-of-the-art predictive algorithms. Our goal is to create personalized engaging shopping experiences with a suite of Brand Shopping Experience products (e.g., Stores, Posts and Brand Follow) that will incentivize brands’ discovery and the creation of customer-brand relationships.

You will focus on the exciting science problems in Amazon Brand Stores. The value that Stores provides to customers is the ability to browse and discover new and best-selling products curated by their favorite brands, while aiding with discovery of new brands. The Amazon Brand Stores program is becoming increasingly important and is at a strategic intersection between advertising and retail. We provide a compelling destination for brand advertising campaigns, and also enable stores to be organically discovered through the Amazon shopping journey. We operate sophisticated front-end, API and big data technologies across all of Amazon, and we partner with teams across Amazon retail, advertisement, marketplace and core shopping. Millions of shoppers enjoy and interact with our products. Our team is a startup-minded, energetic and passionate group of scientists and engineers who care deeply about building amazing products that shoppers as well as brands love. We are curious about new technologies, collaborative, agile, and customer centric.

In this role, you will propose, implement and test algorithms for Stores recommendation, targeting, sourcing and ranking. You will work closely with engineers generating the statistical models, designing, implementing, and testing the release of scalable and low latency machine learning components into production. You will be owner of the solutions that you create. And these solutions will drive engagement metrics that will directly impact our customers’ shopping experiences, while generating increased brand awareness and customer-brand relationships. Come join us!

PREFERRED QUALIFICATIONS

· Concrete experience in reinforcement learning, computer vision, recommendation systems, or deep learning
· 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 solutions, and Spark.
· Strong proficiency with Java, Python, Scala or C++

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.

Desired profile

BASIC QUALIFICATIONS

· M.S. or Ph.D. in Computer Science, Information Retrieval, Machine Learning, Statistics, Applied Mathematics, Natural Language Processing, or related discipline.
· Breadth and depth knowledge of machine learning algorithms and best practices.
· At least 2 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++.