Company
SAP
Industry
IT
Location
Singapore
Position Type
Student Intern: Data Scientist for Machine Learning Job
Post Date
22 Apr 2019
Employer Description
SAP SE is a German-based European multinational software corporation that makes enterprise software to manage business operations and customer relations. SAP is headquartered in Walldorf, Baden-Württemberg, Germany with regional offices in 180 countries. The company has over 335,000 customers in over 180 countries.
Program Details
Data Scientist for Machine Learning
As a Data Scientist on the team, you will work with SAP product and solution units to bring SAP products to the next level by incorporating intelligence, robotic process automation into its existing portfolio. This will be done using machine learning models and tools available as a part of the SAP product portfolio. You will turn initial models into scalable production APIs on SAP’s cloud platform, which other SAP units, customers and partners can easily integrate into existing and new offerings.
EXPECTATIONS AND TASKS
• Learn and apply robotic process automation tools to existing manual business processes
• Validate machine learning use cases with SAP units through proof-of-concepts
• Build deep learning models into existing SAP products
• Part of global team and IT delivery Unit
Requirements
Required:
• B.S., M.S. or PhD in Computer Science or a related field
• Must have good hands-on on Java Script and Java.
• Hands-on experience on Robotics process automation is a plus
• Familiarity with recent advances in deep learning (convolutional neural networks, recurrent neural networks, reinforcement learning, generative adversarial networks, memory networks etc.)
• Hands-on experience with one or more leading deep learning frameworks (TensorFlow preferred; CNTK, MxNet, Caffe, Theano, Torch etc. a plus)
• Good written and oral communication skills in English; German a plus
• Hands-on experience building models in natural language processing and one additional data domains (image, video, speech, tabular)
• Familiarity with cloud engineering, containerization and dev ops
• Ability to interface with internal and external stakeholders
Optional:
• Familiarity with agile development approach and tools
Application
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