Internship Machine Learning & Predictive Analytics for Heat Pump

Job Description

• During your internship you will analyze large-scale historical data to uncover patterns, correlations, and anomalies that support product reliability improvement.
• You will design and evaluate meaningful new features from raw data; perform correlation and relevance analysis to identify key predictive indicators.
• Furthermore, you will develop and evaluate machine learning models on the Databricks platform to enable early detection of potential product issues and proactive reliability improvement.
• Finally, you will present findings and model results clearly through visualizations and dashboards to support engineering decision-making.

Qualifications

• Education: Master studies in the field of Data Science, Machine Learning, Statistics, Computer Science, Mathematics, or comparable
• Experience and Knowledge: you have strong knowledge of machine learning, feature engineering, statistics, and data preprocessing, as well as experience with Python and common data science libraries; familiarity with Databricks, PySpark, MLflow, or time-series analysis is a plus
• Personality and Working Practice: you are self-driven, curious, and structured in your analytical work; you can independently explore data, develop hypotheses, and clearly communicate complex findings to non-technical colleagues
• Work Routine: hybrid model (on-site presence required at least 2 days per week, mobile working available for the rest)
• Enthusiasm: passionate about applying machine learning to real-world product data
• Languages: very good 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?
Linnan Du (Functional Department)
+49 7153 3068232

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