As market leader in enterprise application software, SAP helps companies of all sizes and industries innovate through simplification. From the back office to the boardroom, warehouse to storefront, on premise to cloud, desktop to mobile device – SAP empowers people and organizations to work together more efficiently and use business insight more effectively to stay ahead of the competition. SAP applications and services enable customers to operate profitably, adapt continuously, and grow sustainably.
Data Scientist - SAP Innovation Center Network
PURPOSE AND OBJECTIVES
The SAP Innovation Center Network is a strategic development entity within SAP, combining software engineering excellence with thought leadership and entrepreneurial spirit to create new markets for SAP. Across various focus clusters and by building on strong teams, we pioneer game-changing solutions in close collaboration with startups, customers & partners in industry and research as well as with other SAP units. To ensure a successful go-to-market, we follow an end-to-end responsibility approach. By exploring unconventional ideas and developing inspiring proofs of concepts, we push the state-of-the-art in technology and its applied fields to provide SAP with foresight into future trends.
As a Data Scientist, you will work in a team of experience experienced researchers and data scientists taking on challenges posed by the SAP customers and product units. You will have the chance to work with the richest data sets available in the world addressing real-world problems. Your primary goal will be to implement state of the art algorithms and to develop new approaches and technologies for deriving value from our customers’ real business challenge. You will have a chance to select and implement the best technologies and approaches based on your own experience, judgement, and experimentation results. This role combines (1) experience with machine learning with (2) practical knowledge of working with scalable platforms for processing of huge data sets, and (3) ability to understand the data, associated processes and business implications from different domain, (4) scaling from minimum viable product up to shippable production code.
EXPECTATIONS AND TASKS
• Create data models and algorithms from huge volumes data
• Explore, understand, and implement most recent algorithms and approaches for supervised and unsupervised machine learning
• The candidate will be part of engineering team solving and creating algorithms, which can be further used by enterprise applications
• Comfortably handle multi-terabyte data sets in scale-up and scale-out environments
• Understand business processes which create and consume data so as to be able to select best approaches, evaluate their performance and asses business relevance
• Create excellence both in terms of results quality and system scalability through continuous evaluation, analysis and refinement of the system implementation
• Communicate the relevance of implemented systems and achieved results in a visual and consistent way
EDUCATION AND QUALIFICATIONS
• M.S. or Ph.D. in Computer Science, Applied Mathematics, Statistics or related field
• Track record of developing novel learning algorithms/systems
• 5 years’ professional experience in statistical modeling, machine learning, or data mining practice
• Candidate should be able to in a multi task creative environment, rapid prototype, and agile development environment.
• Experience with Machine/Deep Learning software packages such as TensorFlow/MXNet/SparkML/R etc.
• Ability to visualize data and present core insights in a clear and compelling way
• Excellent communication, relationship skills and a strong team player
• Able to work onsite in Palo Alto, CA
• Able to travel on customer site
• Experience with big data techniques (such as Hadoop, Spark)
• Hands on experience with deep learning with areas of computer vision, natural language processing techniques etc.
• Strong Industry domain knowledge and experience preferred
• Publication track record on deep learning / machine learning
• PhD degree in Computer Science, Applied Mathematics, Statistics or related field
Requisition ID: 157062