Data Scientist
Optics11 · Deep-Tech
- Work arrangement: on site
- Employment type: Full Time
- Seniority: senior
- Posted:
Job description
Position:
Partial Discharge Data Scientist
Company:
Optics11
Location:
Netherlands
Employment type:
On-site
Short Summary:
We are looking for an experienced Data Scientist to develop advanced analytics for our partial discharge monitoring and predictive maintenance platform. You will work closely with cross-functional teams to design, develop, and deploy advanced algorithms that predict energy infrastructure failures.
Responsibilities:
- 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.
- Analyse large-scale sensor, time-series, and operational datasets to identify meaningful patterns and improve monitoring platform performance.
- Develop signal-processing, feature-engineering, statistical-modelling, and machine-learning pipelines.
- Collaborate with software and platform engineers to integrate algorithms into the cloud monitoring platform and edge environments.
- Monitor deployed algorithm performance and contribute to model maintenance, retraining, and continuous improvement.
Requirement:
- 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.
- M.Sc. or Ph.D. degree in a relevant discipline in science or engineering.
Benefits:
- Competitive salary and benefits package.
- Enjoy regular team activities and company events.
- Fresh team lunches provided 3 times/week.
Partial Discharge Data Scientist
Company:
Optics11
Location:
Netherlands
Employment type:
On-site
Short Summary:
We are looking for an experienced Data Scientist to develop advanced analytics for our partial discharge monitoring and predictive maintenance platform. You will work closely with cross-functional teams to design, develop, and deploy advanced algorithms that predict energy infrastructure failures.
Responsibilities:
- 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.
- Analyse large-scale sensor, time-series, and operational datasets to identify meaningful patterns and improve monitoring platform performance.
- Develop signal-processing, feature-engineering, statistical-modelling, and machine-learning pipelines.
- Collaborate with software and platform engineers to integrate algorithms into the cloud monitoring platform and edge environments.
- Monitor deployed algorithm performance and contribute to model maintenance, retraining, and continuous improvement.
Requirement:
- 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.
- M.Sc. or Ph.D. degree in a relevant discipline in science or engineering.
Benefits:
- Competitive salary and benefits package.
- Enjoy regular team activities and company events.
- Fresh team lunches provided 3 times/week.
Skills
- deep_learning
- ml
- numpy
- pandas
- python
- pytorch
- scikit_learn
- scipy
- statistical_analysis
- tensorflow
Languages
EN
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