We are looking for a curious and motivated recent graduate to join Polytech and help us build out our machine learning and data analysis capabilities within blade condition monitoring. If you are early in your career, excited about applying ML to real-world sensor data, and want to contribute to the green transition through smarter wind turbine technology, we'd like to hear from you!

About the position

As our new Junior Data Analyst, you will support analysis and insight generation from Polytech's blade condition monitoring solutions for the global wind turbine industry. Our solutions combine proprietary fiber optic FBG sensors and optical interrogators with advanced data analysis and machine learning — supporting structural health monitoring, load measurement, and improved turbine reliability.

You'll work closely with experienced colleagues across R&D, Product Management, Customer-facing teams, and Operations, helping turn large volumes of measurement data into meaningful indicators, models, and visualizations that support customer projects and internal product development. Part of the role will also include data analysis for our fiber optic interrogator production and calibration, supporting transparency, quality, and continuous improvement of our measurement systems.

This is a great opportunity for a fresh graduate to apply and grow ML skills on real, messy, high-value industrial data — with strong mentorship from senior colleagues along the way.

Key responsibilities and tasks

• Support analysis of blade condition monitoring data from fiber optic sensing systems (FBG) and related measurement sources
• Prepare, clean, and structure datasets (time series/signal data, metadata, events) for analysis and modeling
• Explore data to identify trends, anomalies, and patterns across turbines, blades, and operating conditions
• Help develop, train, and validate machine learning models and health indicators (e.g., anomaly/event detection, load and strain estimation, stability monitoring)
• Assist in experimenting with and evaluating ML approaches for signal classification, forecasting, or predictive maintenance use cases
• Create clear dashboards, plots, and customer-ready visualizations that communicate insights and model outputs effectively
• Support investigations of unusual signals or field events together with senior analysts and domain experts
• Contribute to data analysis and ML-related tasks connected to fiber optic interrogator production and calibration (e.g., performance trends, calibration consistency, test results)
• Help document analysis and modeling methods, data assumptions, and results in a structured way to support reuse and consistency
• Collaborate with cross-functional teams (optics, mechanics, software, product) and contribute a "data and ML-first" perspective

Your qualifications and skills

• BSc or MSc degree in Engineering, Data Science, Machine Learning, Physics, Applied Mathematics, Statistics, or a related field
• Coursework, projects, or thesis work touching on machine learning, statistics, or signal processing is a strong plus
• Interest in working with measurement/sensor data (time series, signals, noisy real-world datasets)
• Basic to intermediate experience with Python for data analysis and ML (e.g., pandas/numpy/matplotlib, scikit-learn; exposure to deep learning frameworks like PyTorch or TensorFlow is a bonus); MATLAB is also relevant
• Understanding of core analytical concepts such as statistics, trends/variation, and model validation
• Interest in renewable energy, wind turbines, or condition monitoring is an advantage
• Proficiency in English; additional languages are an advantage

Personal qualifications

• You are curious, structured, and enjoy learning by doing
• You like solving problems and are not discouraged by messy data or unclear starting points
• You collaborate well and ask good questions when you need input
• You can communicate results and technical findings clearly, keeping focus on practical value
• You are motivated by contributing to reliable, scalable solutions in the wind industry

Apply for the position

Polytech offers this position in a dynamic company working closely with major players in the wind industry to advance the green transition. You will become part of a team with strong collaboration, expert colleagues, and excellent opportunities to grow your data science and machine learning skills.

If you would like to hear more about the position, feel free to contact Sr. Manager, Software & Analytics, Jesper Worsøe Bønding at jwb@polytech.com or mobile +45 20 69 21 96.

To apply, please submit your application via our application portal. We accept applications in both English and Danish. Please note that applications cannot be accepted by email due to GDPR regulations. At Polytech we value diversity and encourage all qualified applicants to apply.

We process incoming applications on an ongoing basis and will remove the job posting once the right candidate has been found.

Application due 28-10-2026

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