Beschreibung
Job Title: Freelance Data Scientist – Production Optimization (Automotive)
Location: Remote (Client based in Germany)
Contract Type: Freelance
Duration: 6 months (with extension possible)
Language: English (German a plus)
About the Role
We are working with a leading German automotive manufacturer seeking a freelance Data Scientist to drive data-driven optimization of its production processes. The ideal candidate will combine industrial analytics expertise with strong hands-on technical skills, supporting predictive maintenance, yield optimization, and process improvement across manufacturing lines.
Responsibilities
- Analyze manufacturing and sensor data to uncover inefficiencies, bottlenecks, and predictive trends
- Develop, test, and deploy machine learning models for production optimization (e.g. downtime prediction, quality monitoring)
- Design data pipelines and ETL workflows for real-time and batch processing
- Collaborate with domain experts, process engineers, and automation teams to align data insights with operational needs
- Visualize findings and communicate results clearly to technical and non-technical stakeholders
- Support the deployment and monitoring of models in production environments
Requirements
- 5+ years of experience in data science, with at least 2 years in a manufacturing or industrial context
- Strong experience with Python (including Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow or PyTorch)
- Proficient in SQL and data wrangling from structured and time-series sources
- Experience with cloud platforms (AWS, Azure, or GCP) and services like S3, Lambda, BigQuery, etc.
- Familiar with Apache Airflow, Docker, and MLflow or equivalent MLOps tools
- Expertise in data visualization (e.g. Plotly, Dash, Power BI, Tableau, or Grafana)
- Understanding of industrial protocols and sensor data formats (e.g. OPC-UA) is a plus
- Familiarity with manufacturing KPIs is a plus (OEE, cycle time, scrap rate, etc.)
- Strong communication skills and experience working with cross-functional teams
Location: Remote (Client based in Germany)
Contract Type: Freelance
Duration: 6 months (with extension possible)
Language: English (German a plus)
About the Role
We are working with a leading German automotive manufacturer seeking a freelance Data Scientist to drive data-driven optimization of its production processes. The ideal candidate will combine industrial analytics expertise with strong hands-on technical skills, supporting predictive maintenance, yield optimization, and process improvement across manufacturing lines.
Responsibilities
- Analyze manufacturing and sensor data to uncover inefficiencies, bottlenecks, and predictive trends
- Develop, test, and deploy machine learning models for production optimization (e.g. downtime prediction, quality monitoring)
- Design data pipelines and ETL workflows for real-time and batch processing
- Collaborate with domain experts, process engineers, and automation teams to align data insights with operational needs
- Visualize findings and communicate results clearly to technical and non-technical stakeholders
- Support the deployment and monitoring of models in production environments
Requirements
- 5+ years of experience in data science, with at least 2 years in a manufacturing or industrial context
- Strong experience with Python (including Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow or PyTorch)
- Proficient in SQL and data wrangling from structured and time-series sources
- Experience with cloud platforms (AWS, Azure, or GCP) and services like S3, Lambda, BigQuery, etc.
- Familiar with Apache Airflow, Docker, and MLflow or equivalent MLOps tools
- Expertise in data visualization (e.g. Plotly, Dash, Power BI, Tableau, or Grafana)
- Understanding of industrial protocols and sensor data formats (e.g. OPC-UA) is a plus
- Familiarity with manufacturing KPIs is a plus (OEE, cycle time, scrap rate, etc.)
- Strong communication skills and experience working with cross-functional teams