Senior Applied Scientist

Job ID: 695744 | Amazon Europe Core SARL - LUX

DESCRIPTION

Amazon's Retail business is growing at an exhilarating pace and customers recently ranked Amazon #1 in the American Customer Satisfaction Index (ACSI) – but it is still “day one”. The EU Home Innovation Program team (EUHIP) is on a mission to reinvent how EU customers discover and purchase products for their Home and personal spaces. These are some of the most personal, meaningful purchases customers make, as they create the homes and daily living experiences that they and their families love. But these are complicated decisions, as they are often emotional or have to do with taste, which each of which is hard to quantify.
As a senior applied scientist, you will invent, build and deploy state of the art machine-learning models and systems to enable and enhance the team's mission—real world incarnations of some of the most difficult academic problems. You will work with Amazon’s data sets, develop a long-term scientific agenda, initiate and lead scientific projects and mentor applied scientists. You will partner closely with our engineering teams, present your work to product and engineering teams at Amazon, publish scientific papers and apply for patents for your inventions.

Responsibilities:
· Advance exploratory research projects in machine learning and related fields to create highly innovative customer experiences;
· Analyze large amounts of data to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities;
· Validate models via statistically rigorous experiments across millions of customers;
· Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale;
· Technically lead and mentor scientists.
Our team is located in our European headquarters in Luxembourg, in the heart of Europe.


About Luxembourg:
The Grand Duchy of Luxembourg is a diverse and multicultural country located in the heart of Europe, bordered by France, Belgium and Germany, with a total population of around half a million. Luxembourg has Luxembourgish, French and German as national languages, with English spoken by the many expatriates and most locals. Luxembourg is known for banking, steel and a number of EU institutions plus an increasing number of technology-centric organizations. Luxembourg boasts a rich cultural scene and a high standard of living.

BASIC QUALIFICATIONS

· Ph.D degree in Computer Science, Mathematics, Statistics, or related quantitative field
· Strong technical credentials, with at least 5 years of professional or post-doctoral experience working in a relevant field: machine learning, deep learning, recommendation systems, information retrieval, natural language understanding, robotics, statistics, computer vision etc.
· Significant peer-reviewed scientific contributions in premier journals and conferences.
· Solid fundamentals in problem solving, algorithm design, complexity analysis, mathematics and statistics.
· Proficiency in a major programming language (Python, Java, Scala or similar).
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.


PREFERRED QUALIFICATIONS

· Demonstrated track record of project delivery for large, cross-functional, cross-organizational projects that are customer facing, handling gigabyte and terabyte-size datasets.
· Practical experience with big-data processing libraries, eg. Apache Spark, Apache Beam, Apache Pig, Hadoop or similar
· Practical experience with building and evaluating deep-learning models using major libraries eg: mxNet, TensorFlow, Keras or similar
· Experience in defining research vision and getting buy-in from senior research and business leader across the company.
Take a look at https://www.aboutamazon.com/research to learn more about research highlights and publications from the Amazon science teams.

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.