Industrial Data & ML Engineer for Asset Optimization

Camlin; Parma; Presencial; EUR 65.000 - 95.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Food vouchers

Training support

Discounted gym membership

Wellness programs

Kudos recognition tool

Descripción de la vacante

Camlin is a global technology leader focused on creating value through engineering and design. As a Data & ML Engineer, you will turn industrial data into valuable product capabilities, collaborating with engineers, product teams, and domain experts to solve real-world problems.

You will work on data engineering, statistical modeling, machine learning, and practical implementation to deliver reliable data-driven solutions for asset monitoring, predictive maintenance, forecasting, and

Formación

• Experience with Python, SQL and ML model development.
• Ability to translate industrial data into product capabilities.
• Strong collaboration with engineering and domain teams.

Responsabilidades

• Translate product and engineering challenges into data-driven solutions.
• Analyze complex datasets to identify patterns and opportunities.
• Develop and evaluate ML models for asset monitoring and predictive maintenance.
• Build and maintain data pipelines and tooling.
• Turn analytical findings into practical, maintainable implementations.

Conocimientos

Python

SQL

Data analysis

Machine learning

Statistical modeling

Data pipelines

Git

Testing

Documentation

Model evaluation

Herramientas

TensorFlow

Scikit-learn

Pandas

Airflow

Descripción del empleo

Camlin is a global technology leader focused on creating value through engineering and design. As a Data & ML Engineer, you will turn industrial data into valuable product capabilities, collaborating with engineers, product teams, and domain experts to solve real-world problems.

You will work on data engineering, statistical modeling, machine learning, and practical implementation to deliver reliable data-driven solutions for asset monitoring, predictive maintenance, forecasting, and