Partial Discharge Data Scientist – Edge & Cloud ML

Optics11; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Competitive salary and benefits

Job summary

Optics11 in Amsterdam, a deep-tech company in fiber-optic sensing, is seeking an experienced Data Scientist to develop analytics for partial discharge monitoring and predictive maintenance.

You will translate challenges into scalable data-driven solutions, collaborating with embedded, software, and hardware teams. You will deploy algorithms to cloud and edge environments, and contribute to model maintenance and improvements.

Qualifications

• 3+ years of professional experience in data science focusing on sensor data analysis.
• Experience with real-time or edge computing is a plus.
• Strong foundation in mathematics, physics, and data modelling.
• Ability to deploy ML models in production or cloud environments.
• Experience with time-series and signal processing.
• Ability to translate data patterns into physical system insights.

Responsibilities

• Design, develop, validate, and maintain algorithms for sensor data analysis and predictive analytics.
• Translate requirements into production-ready algorithms.
• Analyze large-scale sensor and time-series data to identify patterns and improve platform performance.
• Develop signal-processing, feature-engineering, statistical-modeling, and ML pipelines.
• Collaborate with software and platform engineers to deploy algorithms to cloud and edge environments.
• Monitor deployed models and contribute to retraining and improvement.

Skills

Time-series analysis

Signal processing

Statistical modelling

Machine learning

English communication

Education

M.Sc. or Ph.D. in science or engineering

Tools

Python

Pandas

NumPy

SciPy

scikit-learn

PyTorch

TensorFlow

JAX

Job description

Optics11 in Amsterdam, a deep-tech company in fiber-optic sensing, is seeking an experienced Data Scientist to develop analytics for partial discharge monitoring and predictive maintenance.

You will translate challenges into scalable data-driven solutions, collaborating with embedded, software, and hardware teams. You will deploy algorithms to cloud and edge environments, and contribute to model maintenance and improvements.