Intern / Thesis student (f/m): Time Series Analysis & Causal Inference Job

Job description

Requisition ID: 162967
Work Area: Software-Research
Location: St. Leon-Rot
Expected Travel: 0%
Career Status: Student
Employment Type: Limited Full Time

COMPANY DESCRIPTION

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.

PURPOSE AND OBJECTIVES

In general we want to use more intelligent methods for root cause analysis, using comprehensive intelligent analysis (machine learning). Furthermore, many data are also available as Time Series, so that Pattern Detection, Time Series Analysis, Anomaly Detection will occupy a larger space.

Specifically we are talking about multiple time series from system environments. The goal is to run these systems reliable, available and performant and monitor the systems to avoid outages, slow response times etc. to also fulfill SLA´s (Service Level Agreements).

We already have some students working on similar topics and we also have a cooperation with the chair of Hasso Plattner and his PhD students.

EXPECTATIONS AND TASKS

The focus of this Master Thesis is on Intervention Analysis, Survival Analysis, Outlier Detection, Anomaly Detection etc. and on the correlations and causal dependencies between the different time series, but there is still room for a specification of the topic in agreement with the coaching professor and the desires of the student.

EDUCATION AND QUALIFICATIONS / SKILLS AND COMPETENCIES

·  Student (f/m) at a university or a university of applied sciences with preferred fields of study: Machine Learning, Data Science, Advanced Data Analytics
·  Computer skills: R, Python, (Tensorflow, MXNet)
·  Language skills: fluent in English and German, both written and spoken
·  Soft skills: motivated for challenging tasks; curious to learn new technologies and methods

Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please describe as well your experience and skills in foreign languages and computer programs / programming languages.

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SAP'S DIVERSITY COMMITMENT

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