Data Scientist - Prime Video Efficiency Platform

Key Skills

Python Programming, SQL, MATLAB Programming, R Programming, SAS

Job Description

Job ID: 1529783 | Amazon.com Services LLC

DESCRIPTION

Would you like to shape the future of the video entertainment industry for movies, TV and live sports events? Does solving complex problems within large scale systems excite you? If you answered yes, we have an opportunity for you!
Prime Video is disrupting the traditional television and movie industry with a growing library of high-quality media including TV shows, movies and live events including must-see exclusive series like The Boys, Utopia, The Marvelous Mrs. Maisel, The Man in the High Castle, English Premier League, Thursday Night Football and more.
To help a growing organization scale features to Prime Video customers, our Forecasting and Capacity Planning organization is innovating on behalf of our global software development team consisting of thousands of engineers. The team is building a predictive scaling solution that will apply machine learning techniques to develop forecasts on key business dimensions and leverage them to inform and automate scaling across our global software environment.
You will apply your deep knowledge of data science and feature engineering to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions.
You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than pleasing our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies and deep learning algorithms to your solutions. If you crave a sense of ownership, this is the place to be.
We embrace the challenges of a fast paced market and evolving technologies, paving the way to universal availability of content and pushing the envelope of streaming video quality. You will be encouraged to see the big picture, be innovative, and positively impact millions of customers. This is a young and evolving business where creativity and drive will have a lasting impact on the way video is enjoyed worldwide.

BASIC QUALIFICATIONS

• Bachelor's Degree
  
• 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
  
• 2 years working as a Data Scientist
  
• Master's degree in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
  
• 3+ years' experience in state-of-the-art machine learning technologies.
  
• 3+ years professional experience in machine learning, data science, analytics or other quantitative disciplines.
  
• 3+ years' experience with Spark, Python, MXNet.
  

PREFERRED QUALIFICATIONS

• PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
  
• Strong knowledge and development experience with learning algorithms. Experience with the full machine learning lifecycle.
  
• Strong interpersonal and communication skills. Must be able to explain technical concepts and analyses implications clearly to a wide audience, and be able to translate business objectives into actionable analyses.
  
• Publications at top-tier peer-reviewed conferences or journals.
  
• Proven track record of innovation in developing learning algorithms and applying them to to large scale system improvement.