Working Student in Mass Production Semiconductor Data Science (f/m/div.) Gerhard-Kindler-Straße, 72770 Kusterdingen, Germany Part-time Bosch Sensortec GmbH Company Description Bosch Sensortec GmbH develops and markets key technologies in consumer electronics – micro-electro-mechanical sensors (MEMS), solutions and systems for smartphone applications, tablets, video game consoles, wearables, and the Internet of things. The sensors enable devices to recognize their surroundings and to transmit the data collected. MEMS are therefore part of the foundation for a networked world. Bosch Sensortec GmbH is a wholly owned subsidiary of Robert Bosch GmbH. The Bosch Sensortec GmbH is looking forward to your application! Job Description During your assignment you will create algorithms to analyse sensor data statistically from mass production and/or laboratory data. Furthermore, you will create algorithms and pipelines for semiconductor mass production analysis, which includes data mining, statistics analysis and machine learning models. To predict failures you will create machine learning algorithms. Qualifications Education: studies in Computer Science/Data Science or a related technical field with good grades Experience and Knowledge: experienced in programming and data analysis in Python, SQL, Machine Leaning; big data analysis is an advantage (Hadoop, Spark) Personality and Working Practice: you have strong analytical and problem solving skills Work Routine (Office/mobile working): initial 2 weeks in the office for onboarding and later at least once per month office presence Languages: business fluent in English Additional Information Start: according to prior agreement Duration: 6-12 months – 15 h/week Requirement for this working student position is the enrollment at university. Please attach your CV, transcript of records, enrollment certificate 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? Victor Castro de Morini (Functional Department) 49 172 177 9939 LI-DNI