Job Description
The intern will support the definition and development of routines to detect performance anomalies by comparing a selected “gold” reference vehicle with other vehicles in the fleet.
Responsibilities
- Contribute to the use of the gold vehicle as a baseline for training machine learning and deep learning models
- Support the analysis, cleaning, and structuring of large datasets that are currently unorganized or only partially usable
- Assist in preparing data for model training
- Help connect engineered data to product issue resolution activities
- Support performance comparisons across fleet vehicles
- Contribute to preliminary root cause analysis activities
Profile Description
- Students or recent graduates in IT engineering, computer science, data science, applied mathematics, or related fields
- Interest in machine learning and data engineering
- Basic understanding of data analysis concepts
- Awareness of the impact of data quality on machine learning results
- Familiarity (even at academic level) with handling large or unstructured datasets (preferred)
- Interest in anomaly detection, diagnostics, or product performance analysis
- Curious and analytical mindset
- Attention to detail and willingness to learn
- Ability to collaborate in multidisciplinary teams within a structured, engineering-driven environment
- English language skills (good knowledge to advanced)
We Offer
Contact Person Talent Acquisition: Mariele Lo Bianco
Interested?
If so, please use our online application tool to send your application to AVL!