Data Scientist - Kindle Content

Luxembourg City

Ref: 680057

At Amazon, we get our energy from inventing on behalf of customers. Success is measured against the possible, not the probable.
We are inventors that are working to build the best solutions to unique problems through breakthrough technology – for example, Kindle has revolutionized the way customers consume digital content. Working on the EU Amazon Content team will be unlike any job you have had.

The Kindle EU Content team is looking for an experienced Data Scientist based in the Luxembourg Office.
This role requires an individual with excellent analytical abilities, deep knowledge of predictive analytics (supervised, unsupervised learning) and Optimization techniques. The successful candidate should be able to learn by doing and apply methods quickly, iterating as necessary to drive business value.

We are looking for someone with big love for big data. You will help us solve complex business problems and challenges we are facing by using top-of-the-line machine learning techniques and practices. This is a hands-on, high-impact technical position. You will spend most of your time writing code and wrangling data.
The successful candidate will also be a self-starter, be comfortable with ambiguity, have strong attention to detail, and will be comfortable accessing and working with data from multiple sources.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. We offer a competitive salary and stock units, we offer a whole host of other benefits, including an employee discount and pension scheme.

We are committed to keeping compensation fair and equitable.

Basic Qualifications

Basic qualifications

  • Advanced degree in computer science, statistics, information systems, economics, mathematics or similar
  • 5+ years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models
  • Strong proficiency in SQL and R/Python is required
  • Very strong self-learning skills. Ability to pick up and adapt modeling methods from other disciplines or leverage methods from colleagues in other departments.
  • Practical understanding and hands-on experience with the following:
  • * Supervised learning methods (linear and logistic regression, generalized linear models, decision trees, random forests, support vector machines, graphical models, neural networks / deep learning, etc.).
  • * Unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components, etc.).
  • * Mathematical optimization (mixed integer programming, linear programming, stochastic programming/optimization discrete optimization convex optimization, reinforcement learning, etc.).

Preferred Qualifications

Preferred qualifications

  • PhD in a quantitative field such as Economics, Mathematics, Information Systems, Statistics, Operations Research or Computer Science
  • Experience in Computer Vision and Deep Learning
  • Working knowledge of reinforcement learning applications
  • Verbal/written communication & data presentation skills, including an ability to effectively communicate with both business and technical teams.
  • Understanding of our technology environment, and the performance and scalability issue associated with certain applications.
  • Superb attention to details and organizational skills

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