Partial Discharge Data Scientist
On-siteAmsterdam, North Holland, The Netherlands
Job Summary
Design, develop, validate, and maintain algorithms for sensor data analysis, partial-discharge monitoring, and predictive analytics. Translate complex business and engineering requirements into robust, production-ready algorithms by analyzing large-scale sensor, time-series, and operational datasets to identify meaningful patterns. Develop signal-processing, feature-engineering, statistical-modelling, and machine-learning pipelines, then collaborate with software engineers to integrate these solutions into cloud and edge environments. Monitor deployed algorithm performance and contribute to model maintenance, retraining, and continuous improvement. This role supports Optics11's deep-tech R&D team in enabling next-generation acoustic emission monitoring for energy infrastructure and underwater security.
Required Qualifications
- Strong professional experience with Python and commonly used scientific and data-science libraries (e.g., pandas, NumPy, SciPy, scikit-learn)
- Strong foundation in statistical analysis, algorithm development, machine learning, and data modelling
- Practical experience analysing sensor signals and time-series data
- Solid understanding of signal-processing techniques such as filtering, denoising, spectral analysis, Fourier or wavelet transforms, and dimensionality reduction
- Experience developing, validating, and deploying machine-learning models in production or cloud environments
- Ability to connect patterns in data with physical processes and real-world system behaviour
- Experience with at least one deep-learning framework, such as PyTorch, TensorFlow, or JAX
- Ability to write clear, modular, tested, and maintainable Python code
- Experience contributing to end-to-end data-science or ML projects, from problem framing and experimentation to deployment and monitoring
- At least 3 years of professional experience in data science with a focus on sensor data analysis
- M.Sc. or Ph.D. degree in a relevant discipline in science or engineering
- Strong analytical and problem-solving skills
- Solid understanding of mathematics and physics, with the ability to apply theory to real engineering problems
- A pragmatic, hands-on mindset and willingness to work with imperfect real-world data
- Strong verbal and written communication skills in English
- Ability to work independently, take ownership, and collaborate effectively across disciplines
- Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service)
Desired Qualifications
- Previous experience in partial discharge, acoustic emission or electrical signal processing
- Familiarity with real-time systems, edge computing, or predictive maintenance solutions
- Knowledge of time-series and general-purpose databases such as QuestDB, MongoDB, or PostgreSQL
- Experience with experiment tracking, dataset or model versioning, and reproducible ML workflows
- Experience with GPU computing, CUDA, model optimization, or real-time edge deployment
- Familiarity with MLOps practices, automated testing, CI/CD, and production model monitoring
- Dutch language skills
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