GreenPowerMonitor, a DNV company, is at the heart of global energy transformation. We use data-driven digital solutions to optimize the performance of renewable energy installations around the world. Our work contributes to a more diverse and sustainable global energy mix.
We are looking for a motivated and skilled Data Scientist to join our team and contribute to the support and development of data-driven solutions in the renewable energy sector. If you are passionate about data, fluent in Python, and experienced in statistics, time series analysis, and boosting techniques, we want to hear from you!
Key Responsibilities:
- Analyze time series data and perform data quality control for wind, solar, and storage technologies.
- Apply statistical and machine learning techniques to uncover insights from complex datasets.
- Collaborate with cross-functional teams to integrate analytical outputs into operational workflows.
- Train and evaluate models with effective hyperparameter tuning and result validation to support business decisions.
- Use Kubernetes to manage and deploy machine learning workflows in containerized environments.
- Work with databases such as MongoDB, ClickHouse, and PostgreSQL, for data storage and processing.
This is a unique chance to apply your data science skills to real-world challenges in renewable energy. You'll work with advanced tools and technologies, contribute to impactful projects, and help accelerate the global shift toward a sustainable energy future.
Our benefits package is specifically designed to support your physical, financial and social wellbeing:- Great atmosphere of working together with professionals and some of the most engaged and knowledgeable people in the industry.
- Guidance from colleagues through coaching, mentoring and participating in international networks.
- Numerous opportunities to advance your professional skills and technical expertise through individual competence development plans and tailored training.
- Multiple country specific lifestyle benefits, including health insurance, pension plan, flexible work schedule, trainings, etc.
- Be part of a world growing and renowned organization with origins dating back to 1864.
To thrive and succeed, you have:
- Degree in Engineering, Mathematics, or Computer Science.
- Strong proficiency in Python, including libraries such as NumPy, Pandas and Scikit-learn.
- Solid foundation in applied statistics, including the series analysis, clustering, distribution analysis, and hypothesis testing.
- Practical experience with machine learning algorithms, especially clustering, regression and boosting methods (e.g. XGBoost, LightGBM, CatBoost).
- Experience in hyperparameter tuning and model performance optimization.
- Hands-on experience with time series modeling and analysis.
- Working knowledge of databases such as MongoDB, ClickHouse, or PostgreSQL.
Proficient in Git for version control and collaborative development.
Will be a plus:
- Familiarity with AutoML tools to streamline model development.
- Basic Knowledge of Kuberflow for orchestrating machine learning workflows.
- Experience with cloud platforms (Kubernetes, AWS, Azure) and containerization tools like Docker is a plus.
- Prior experience int he renewable energy domain is a strong advantage.
- Deep learning techniques and frameworks such as TensorFlow or PyTorch is a plus.
As a person, you demonstrate strong analytical thinking, curiosity, and a problem-solving mindset. You can work both independently and collaboratively, communicating complex finding clearly to nontechnical stakeholders. A high level of attention to detail, adaptability, and a passion for continuous learning are essential, especially in fast evolving environments like renewable energy. Strong teamwork, ownership, and a proactive attitude toward challenges and innovation are key to thriving in this role.
