SAP Data Scientist - Global CoE Technology Job in Walldorf/St. Leon-Rot, Germany

Requisition ID: 169631

Work Area: Customer Service and Support

Location: Walldorf/St. Leon-Rot

Expected Travel: 0 - 50%

Career Status: Professional

Employment Type: Regular Full Time


SAP’s vision is to help the world run better and improve people’s lives.

As the cloud company powered by SAP HANA®, SAP is a market leader in enterprise application software, helping companies of all sizes and industries run better. SAP empowers people and organizations to work together more efficiently and use business insight more effectively. SAP applications and services enable our customers to operate profitably, adapt continuously, and grow sustainably.

At SAP, we believe in the power of collaboration and empower our employees to perform at their best in an environment that encourages free and open expression of ideas. You’ll work alongside creative thinkers who share your interests, while turning big ideas into reality for our customers. With innovative job training, mentors to help you grow, and the flexibility to balance your work and personal life, you’ll be able to get more out of your career. It’s no wonder that some of the sharpest minds from around the world are working for a company that is consistently recognized as a global top employer.

Now it’s your turn to take the next step and help make the world Run Simple.


Within SAP Digital Business Services, the Global Center of Expertise (CoE) Technology builds end-to-end serviceability and its intelligent automation across SAP technology stacks. Our foundation for this is the data-driven learning cycle which leads us to augmented intelligent service deliveries.


As a Data Scientist you will work with the actual and historical detailed technical configuration and usage data stored at SAP of most of customer’s SAP systems. Together with lead technology and service experts you translate our customers' needs for business continuity and total cost of ownership into mathematical models, develop algorithms, data mining flows and applications to overcome these challenges, and help our customers directly to understand and implement the results of the analysis.

For this task, we are looking for passionate and communicative people who enjoy working in a team. In this role, you will experience a variety of challenges and tasks. You will consult SAP internal and our customers to apply state of the art modern data analytics and Machine Learning methodologies. Since we provide services at our customer sites, business travel will be part of this role.

As an Data Scientist in Global CoE Technology, you can accelerate your functional career in a highly professional environment that supports original thinking, rewards initiative and recognizes outstanding performance. Best of all, you become part of a rich, stimulating environment in which you have daily access to technical experts, subject-matter experts, and close working relationship with development.

Based on all your experiences and learnings out of the customer facing service deliveries you will develop for example intelligent tooling and leading practices for fast, safe, and predictable outcomes. This supports other Digital Business Services colleagues to be more efficient in their service delivery, or even leads to supervised machine trained applications.


  • You carry out complex analyzes on issues during build and run phase of SAP’s Technology with a focus on S/4 HANA, HANA, Data Hub and Cloud Platform

  • You apply explorative methods for pattern recognition, determination of relationships and identification of abnormalities

  • You interpret the analysis results as well as their visualization and communication

  • You select and apply suitable methods, from scorecards to state-of-the-art machine learning algorithms to best match our service requirements

  • You develop analytical predictive models and optimize them continuously

  • You support existing models and their continuous improvement


Data Science and Machine Learning skills

  • Strong background in mathematics and statistics

  • Excellent understanding of statistical and technical methods to produce relevant insights out of massive amounts of data

  • Mathematical modelling: R, Python

  • Knowledge of Artificial Intelligence / Machine Learning concepts and tools

  • Development experience with Machine Learning tools and environments

  • Programming: SQL, JavaScript/Java

  • Experience with Deep Learning Frameworks such as TensorFlow, Caffe, Theano

  • Big Data experience (Hadoop)


  • Ability to capture customer requirements and translate them into software specifications

  • Ability to present complex information in a clear and precise manner; with non-technical audience

  • Presentation skills – ability to create professional presentations, handle proper setup of location, use technical/ visual aid, have adequate body language and vocabulary, proactively engage with the customer and handle questions

Personal skills

  • Fluent in English and German is mandatory

  • Master or Bachelor degree or equivalent(Mathematics, Computer Science, Informatics, natural science, engineering)

  • Strong problem solving and consulting capabilities

  • Integrity, excellent team player, self-motivated, passionate and drive for long-term commitment

  • Ability to work well in a multicultural and multinational environment


  • 3-4 years of relevant work experience


To harness the power of innovation, SAP invests in the development of its diverse employees. We aspire to leverage the qualities and appreciate the unique competencies that each person brings to the company.

SAP is committed to the principles of Equal Employment Opportunity and to providing reasonable accommodations to applicants with physical, sensory and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please contact us at . Requests for reasonable accommodation will be considered on a case-by-case basis.

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