Production ML Data Scientist – Time-Series Power Grids

Nexus Grid - a DNV Company; Arnhem; Hybrid; EUR 60,000 - 90,000; Full time

Job summary

Nexus Grid, a DNV Company, is seeking a Data Scientist to turn raw signal data into actionable insights for grid operators. You will work on analytics and AI models behind PulseIQ, covering fault location, pre-fault detection, asset health and predictive analytics.

You will develop, validate and deploy models on time-series data from Smart Cable Guard installations, applying ML techniques to create new features and insights that drive product value.

Qualifications

• Master's degree or PhD in data science, electrical engineering, physics, mathematics or a related field.
• Experience developing and validating machine learning or statistical models.
• Strong programming skills in Python and common data science libraries.
• Experience working with time-series or sensor data.
• Structured, curious approach and the ability to explain complex results simply.

Responsibilities

• Develop, validate and improve models for fault detection, localization and asset condition assessment.
• Analyze large volumes of time-series and event data from Smart Cable Guard installations.
• Apply machine learning and AI techniques to create new insights and product features.
• Work with product, engineering and customer teams to turn models into reliable, usable features.
• Monitor model performance in production and improve accuracy over time.
• Communicate findings clearly to technical and non-technical stakeholders, including customers.

Skills

Python

Time-series

Statistical modeling

Communication

Education

Master's or PhD in data science / EE / physics / math

Tools

scikit-learn

TensorFlow

PyTorch

Job description

Nexus Grid, a DNV Company, is seeking a Data Scientist to turn raw signal data into actionable insights for grid operators. You will work on analytics and AI models behind PulseIQ, covering fault location, pre-fault detection, asset health and predictive analytics.

You will develop, validate and deploy models on time-series data from Smart Cable Guard installations, applying ML techniques to create new features and insights that drive product value.