Dateningenieur

About Us

Are you looking for a secure and permanent job in a solid company in the pharmaceutical sector? Varied tasks? A trusting working atmosphere and a team that values your effort and commitment? Are you a Data Engineer living in or around Mannheim? Then join our experts at Randstad professional solutions – from professionals for professionals! Apply now easily and quickly online! We value equal opportunities and welcome applications from people with disabilities.

Responsibilities

• Design and implementation of state-of-the-art AI/ML models, e.g. Predictive Maintenance, for the optimization of complex manufacturing processes
• Analysis of large amounts of data from pilot plants using statistical methods and big data time series analyses
• Conception, execution, and statistical evaluation of measurement setups in development and production machines
• Technical leadership of sub-projects, including resource planning, schedule control, and coordination of external partners
• Continuous further development and maintenance of productive ML models as well as optimization of data flows between hardware and software

Qualifications

• Completed studies in process engineering, data science, physics, computer science, or a comparable field
• Sound professional experience in process/product development, ideally in the regulated environment of medical technology
• Confident handling of Python and knowledge of hardware-related programming with C++
• Experience with ML libraries such as TensorFlow or Keras
• In-depth knowledge of automated data acquisition and time series analyses
• Knowledge in the implementation of Machine Learning Operations (MLOps) in an industrial context
• Structured way of working and strong problem-solving skills
• Ability to precisely document complex issues

Benefits

• Performance-oriented salary package depending on qualifications and professional experience
• Attractive social benefits, such as holiday and Christmas bonuses
• Company pension plan subsidy after the probationary period
• Vacation entitlement of up to 30 days per year
• Competence development through diverse e-learnings
• Definition of career goals
• Monthly changing employee offers, e.g. for technology, fashion, cars, etc.