Senior Data Scientist

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Senior Data Scientist

Organization: 
AGT International
Country of Position: 
Germany
Contact Name: 
Christian Debes
Subject Area: 
Machine Learning for Signal Processing
Start Date: 
December 13, 2016
Expiration Date: 
March 31, 2017
Position Description: 

Job Opening – Darmstadt (Frankfurt area)/Germany, December 2016

AGT is all about striving for the best Analytics for the Internet of Things!

Our teams are professional and fearless – our working environment is energized, sweeping and demands use of cutting edge technology. We are never behind. Out of the box thinking and creativity in everything we do. Being always in search of new ideas turning into great new features and products, we would love to meet and welcome team members joining the ride and driving us forward. We are looking for

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AGT is passionate about creating a unique analytics engine to answer highly valuable business questions across various industries. Our focus is on innovative and new technologies for Internet of Things, specifically for sports and entertainment. We provide the opportunity to drive ideas from conception to products which are deployed in the market. You will be given the opportunity to work directly with our customers and partners to solve their data-driven problems and needs where you will be working with large as well as unique and complex data sets from traditional data sources and from the rapidly growing world of IoT sensors.

With your PhD in machine learning or signal processing you will join a larger team of like-minded and talented people, eager to squeeze out informational value from various data sources and explore new ways. Your contributions will end up in exciting products in the domain of sports and entertainment and you will be given the opportunity to work on a variety of tasks and develop your skills in many area ranging from new and exciting analytics technologies to collaboration with agile development teams, Product Management, Marketing and Sales.

We will provide you with an environment fostering the autonomy of data scientists and a good mix between coding, conceptualization and customer engagement.

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