Internship Machine Learning & Predictive Analytics for Heat Pump

Job Description:

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

Candidate Requirements:

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