Machine Learning Scientist

Job description

DESCRIPTION

Our development centre in Edinburgh is responsible for devising and growing innovations for Amazon around the world. Small teams of developers, designers, machine learning scientists and leaders run major parts of Amazon's business, technology and operations. From interactive UI design to large-scale distributed systems and machine learning, we do whatever it takes to deliver great products and experiences for our customers.

Successful candidates will have strong technical ability, a focus on great customer experience, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment.
Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems at huge scale, working on exciting and challenging projects and delivering meaningful results.

Key Responsibilities:
· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment.
· Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems.
· Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
· Promote the culture of experimentation and science at Amazon.

Desired profile

BASIC QUALIFICATIONS

· Masters degree in Computer Science, Mathematics, Physics, Statistics, AI or related quantitative field.
· Experience applying machine learning techniques to business problems.
· Strong computer science grounding in a broad range of algorithms and data-structures.
· Proficiency in an object-orientated programming language (C++, Java, C#, C, Perl/Ruby, etc.)
· Proficiency with mathematical programming environments (R, Matlab, Numpy/Scipy, SAS, etc.)
· Programming skills sufficient to extract, transform, and clean large (multi-terrabyte) data sets in a Unix/Linux environment.
· Excellent critical thinking skills, combined with the ability to present your ideas clearly and compellingly in both verbal and written form.