Data Scientist

DNV; Madrid; Presencial; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

Join DNV, a leader in global energy transformation, as a Data Scientist. In this role, you'll leverage your expertise in Python, statistics, and machine learning to analyze data from renewable energy technologies. You'll collaborate with various teams, utilizing advanced tools to drive impactful projects in sustainability and energy performance optimization.

Servicios

Great working atmosphere

Mentoring and coaching opportunities

Tailored training and development plans

Country-specific lifestyle benefits including health insurance and pension plan

Formación

• 3+ years of experience in data science.
• Strong proficiency in Python and machine learning algorithms.
• Experience in time series analysis and model optimization.

Responsabilidades

• Analyze time series data and perform data quality control.
• Apply statistical and machine learning techniques to complex datasets.
• Collaborate with cross-functional teams and integrate analytical outputs.

Conocimientos

Data Analysis

Machine Learning

Python

Statistics

Time Series Analysis

Cloud Platforms

Containerization

Deep Learning

Educación

Degree in Engineering, Mathematics, or Computer Science

Herramientas

Git

MongoDB

ClickHouse

PostgreSQL

Descripción del empleo

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.

Benefits include:

• Great atmosphere working with professionals and some of the most engaged and knowledgeable people in the industry.
• Guidance from colleagues through coaching, mentoring, and participation in international networks.
• Opportunities to develop your professional skills and technical expertise through tailored training and competence development plans.
• Country-specific lifestyle benefits including health insurance, pension plan, flexible work schedule, and training.

Join a growing, renowned organization with origins dating back to 1864. DNV is an Equal Opportunity Employer, considering all qualified applicants without regard to gender, religion, race, nationality, cultural background, social group, disability, sexual orientation, gender identity, marital status, age, or political opinion. We value diversity and invite you to be part of it.

Qualifications

• 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 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.

Proficiency in Git for version control and collaborative development is required.

Preferred Skills :

• Familiarity with AutoML tools.
• Knowledge of KubeFlow for orchestrating machine learning workflows.
• Experience with cloud platforms (AWS, Azure) and containerization tools like Docker.
• Previous experience in the renewable energy domain is advantageous.
• Knowledge of deep learning frameworks such as TensorFlow or PyTorch is a plus.

Ideal candidates demonstrate strong analytical thinking, curiosity, problem-solving skills, and the ability to communicate complex findings clearly to non-technical stakeholders. Attention to detail, adaptability, passion for continuous learning, teamwork, ownership, and a proactive attitude are essential for success in this role.

Key Skills

Data Analysis, Machine Learning, Python, Statistics, Time Series Analysis, Cloud Platforms, Containerization, Deep Learning

Employment Type : Full-Time

Experience : 3+ years

Vacancy : 1