Data Scientist (m/w/d) – Anomalieerkennung für Recyclinganlagen
Core
Develop and deploy machine learning models for anomaly detection in time series data from recycling machinery to optimize operations and support process analysis.
Role type
Machine learning engineer (anomaly detection)
Builds
Production ML models for industrial IoT software
Domain
Industrial IoT / Recycling technology
Deliverable
production ML models
Required skills
Machine learning, time series analysis, Python (object-oriented), SQL, data modeling, Git, code reviews
Preferred skills
Cloud platforms (AWS), industrial real-time machine data, AI coding assistants
Technologies
Python, scikit-learn, pandas, NumPy, SQL, PostgreSQL, AWS, Git
Responsibilities
Develop, train, and validate machine learning models for anomaly detection; analyze and visualize complex time series data; deploy models to production and set up monitoring; write efficient SQL queries for relational databases; collaborate with domain experts to translate operational challenges into data-driven solutions
Seniority
Mid-level, hands-on IC
