Internship in Data Science

• During your assignment you will delve deeply into the workings of industrial machines analyzing failure modes and performance characteristics to develop a comprehensive understanding of their behavior.
• Your area of responsibility includes cleaning processing and constructing meaningful features from multivariate sensor data sets to create an excellent basis for advanced modeling and analysis.
• Take an active role in visualizing and analyzing complex data sets using time series charts correlation matrices and other exploratory techniques to uncover hidden relationships and interactions between key features.
• Furthermore you will develop hybrid algorithms that combine domain expertise with state-of-the-art analytics AI and machine learning methods to generate actionable insights for predictive maintenance and system optimization from digital twin data.
• From the first day you will accurately evaluate and validate models using labeled data sets and define performance baselines using relevant metrics such as accuracy precision and recall.
• You work on creating scalable templates and integrating them into our digital twin platform to optimize deployment and ensure repeatability across different plants and customers.
• Last but not least you will document methods results and technical workflows in a clear and structured manner to ensure knowledge transfer and the reproducibility of your solutions.

Qualifications :

• Education: studies in mechanical engineering computational engineering computer science physics or comparable
• Experience and Knowledge: strong skills in data analytics frameworks machine learning algorithms (classification regression etc.) Git and proficiency in Python programming is mandatory; experience in vibration monitoring (time and frequency domain analysis) or turbomachinery is preferred
• Personality and Working Practice: you are a self-motivated proactive and responsible person with the ability to work effectively in cross-functional teams
• Languages: business fluent in English

Additional Information :

Start: according to prior agreement
Duration: 6 months

Requirement for this internship is the enrollment at university. Please attach your CV transcript of records enrollment certificate examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.

Need further information about the job
Maitraiyee Tiwari (Functional Department)
49 8
Patrick Schlachter (Functional Department)

Work #LikeABosch starts here: Apply now!

Remote Work :

No

Employment Type :

Full-time