Your Tasks and Educational Objectives
- Provide support to use cases and pilots to evaluate the use of new technologies, e.g. advanced data analytics, artificial intelligence or machine learning
- Co-Development of prototypical machine learning applications (e.g. using Python or R and visualizing the results in Tableau)
- Support in preparation, consolidation, transformation as well as in analysis of process and business data
- Cooperation in the conception and implementation of measures for continuous improvement of data quality and their representation in dashboards using modern visualization tools
- Help with the development and implementation of optimization ideas – from problem analysis to implementation in interdisciplinary teams
Who you are
- Enrolled master student (m/f/d) in computer science, statistics, mathematics or in an equivalent field
- Practical experience with tools for visualizing data (e.g. Tableau) are an advantage
- Ideally first experiences in one of the following fields: Data Science (Data Mining, Data Analysis, Data Visualization) or Machine Learning (Neural Networks, Deep Learning)
- Enjoy working in a team and passion for developing and implementing new ideas and creative concepts
- Fluent in English, both written and spoken
We offer a 4-6 months internship (either voluntary or obligatory). Please apply online submitting a cover letter, your CV, your certificates, your proof of enrollment, your current transcript of records as well as the internship guidelines of your university. Please indicate your earliest possible start date and timeframe in your application.
Your application Internships at Bayer are designed to help you gain experience, learn new things and decide which direction you want your career to go in. You will perform practical tasks under the guidance of experienced members of staff, helping you to enhance your theoretical knowledge in the process.
Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.