Data Scientist

Overview

We are seeking a highly skilled Data Scientist to drive innovation in our partial discharge monitoring and predictive analytics platforms. In this role, you’ll translate complex business and engineering challenges into scalable, data-driven solutions, shaping the future of how we detect, interpret, and act on critical sensor data. You will work closely with cross-functional teams (embedded, software, and hardware) to design, develop, and deploy advanced algorithms that predict energy infrastructure failures.

Optics
11 Energy is the power-grid reliability arm of Optics
11, focused on fiber-optic sensing and analytics for high- and medium-voltage equipment. Our flagship Opti Fender platform delivers ultra-early, EMI-immune partial discharge (PD) detection and precise localization across transformers, cables, GIS/GIL and switch gear. We help TSOs/DSOs and industrial operators move from reactive repairs to predictive maintenance, improving safety, uptime, and total cost of ownership.

• Design and implement advanced algorithms for our partial discharge monitoring platform.

• Translate complex business and engineering requirements into robust, production-ready algorithms.

• Collaborate with data scientists, software engineers, and domain experts to develop data analysis, feature extraction, and signal processing pipelines.

• Explore and analyse large-scale sensor and operational datasets to uncover actionable insights and improve system performance.

• Consult embedded and software teams to optimize algorithm integration into real-time and edge environments.

• Contribute to model validation, performance monitoring, and continuous improvement of deployed solutions.

• Innovative high-tech, international organization.

• The opportunity to work in a cross-functional and interdisciplinary environment.

• A lot to learn and to develop, we stimulate personal development.

• A flat organization, the less hierarchy, the better.

• Expert-level proficiency in Python and common data science libraries (e.g., pandas, Num Py, Sci Py, scikit-learn).

• Strong background in algorithm development, statistical analysis, and data modelling.

• Solid understanding of signal processing techniques (e.g., filtering, denoising, Fourier/wavelet transforms, PCA).

• Experience building and deploying machine learning models.

• Ability to relate data patterns to physical phenomena in real-world systems.

• Deep learning experience with PyTorch, Tensor Flow, or JAX.

• Experience working with big data technologies and cloud platforms (AWS, Azure, GCP).

• Knowledge of database technologies (Quest
  
  DB, Mongo
  
  DB, Postgre
  
  SQL).

• GPU programming experience (CUDA) or real-time edge deployment.

• Strong understanding of clean code structure, design patterns, maintainable code practices, and object-oriented programming.

• C/C++ experience.

• You have at least 3 years of professional experience in data science with focus on sensor data analysis.

• Familiarity with real-time systems, edge computing, or predictive maintenance solutions is a plus.

• Experience contributing to end-to-end ML projects, from problem framing to deployment and monitoring.

• M.Sc. or Ph.D. degree in a relevant discipline in science or engineering.

• Strong analytical and problem-solving skills.

• Excellent practical knowledge of mathematics, physics, data science techniques.

• You have a can-do mentality with no fear of getting your hands dirty when needed.

• You have strong verbal and written communication skills in English.

• You can work independently as well as in a team with well-developed communication skills.

So now you know we re doing awesome projects and if you see you fit the profile, we would like to get to know you. Apply and drop your details or, in case of questions, get in touch with our recruiter Dora Öveges via