Data Scientist

Data Scientist

• Location: Tilburg
• 5+ years of relevant experience
• Experience with time-series data is a must

Your Contribution to a Greener Future

Be part of a team at the forefront of innovation in hydrogen technology and sustainable energy solutions. In this role, you will help develop and optimize advanced electrolyzers—critical components in the transition to green energy. Electrolysis, a key process for hydrogen production, creates a multiphase flow of oxygen and hydrogen gas that directly influences water and temperature distribution within the electrolyzer stack.

Your goal will be to build sophisticated computational models that accurately describe and predict this complex behavior, ultimately driving improvements in efficiency and performance.

What You’ll Do

• Contribute to high-impact projects in the renewable energy sector, focusing on the design and enhancement of electrolyzer systems.
• Play an essential role in advancing sustainable energy technologies to reduce carbon emissions and combat climate change.
• Work within a dynamic, cross-functional SCRUM team of around 10 skilled professionals, including data engineers, data analysts, and data scientists.
• Act as a key connector between data engineering and analytics, fostering effective collaboration and ensuring data-driven decision-making.
• Apply the latest tools and techniques in data science—including machine learning, deep learning, and generative AI—to solve complex problems and accelerate your professional growth.
• Collaborate with stakeholders across different organizational units, including research and digital innovation departments.

What Sets You Apart

• 5+ years of experience in data science, with a proven track record of delivering results in production environments.
• Strong background in working with time-series data.
• Solid knowledge of data science methodologies, including model development, training, validation, and deployment—especially in areas like Machine Learning, AI, and Generative AI.
• Proficiency in data modeling, feature engineering, and data cleaning.
• Hands-on experience with tools and platforms such as Azure Machine Learning, Databricks (and its ML suite), or equivalent.
• Understanding of data governance best practices to ensure data quality, compliance, and structure.
• Familiarity with the SCRUM framework and agile ways of working.
• Proficient in cloud-based programming (Python, SQL, JavaScript) and libraries such as TensorFlow, Pandas, PySpark, and Matplotlib.
• Experience working in DevOps and MLOps environments, including building automated model pipelines and using CI/CD frameworks.
• Comfortable using version control and collaboration tools such as Git and GitHub.
• Proven ability to work collaboratively with data engineers, business analysts, and product owners throughout the project lifecycle.
• Knowledge of various testing strategies (unit, integration, acceptance, functional).
• Passion for mentoring and the ability to guide and support junior team members through technical challenges.