Data Scientist

We are Akkodis. We put the talents, skills and ambitions of our Consultants first. Because we continuously offer you challenging projects, you continue to develop and you can realize your ambitions. This is our view on good employment practices.

The client is leading the way in advancing hydrogen technology and sustainable energy solutions. In this role, you will play a key part in developing and optimizing state-of-the-art electrolyzers, which are essential to the green energy transition. Electrolysis—a critical process for hydrogen production—creates a multiphase flow of oxygen and hydrogen gas, influencing both water and temperature distribution within the electrolyzer stack.

Your objective will be to develop advanced computational models that describe and predict this complex behavior, driving efficiency and performance improvements.

• Contribute to cutting-edge projects in the renewable energy sector, focusing on the development and optimization of electrolyzers.
• Play a key role in advancing sustainable energy solutions, helping to reduce carbon emissions and combat climate change.
• Join a dynamic, cross-functional SCRUM team of 10 skilled data professionals, including data engineers, data analysts, and data scientists.
• Serve as a bridge between data engineering and data analysis teams, ensuring seamless collaboration and data-driven decision-making.
• Utilize the latest data science tools, technologies, and methodologies (such as machine learning, deep learning, and GenAI) to tackle complex data problems and enhance your career prospects.
• Connect to stakeholders in other divisions within the client (Corporate Research, Digital)

What distinguishes you

• 2-5 years of experience in a data science role, with a demonstrated impact on production-level projects.
• Experience with time-series data is a must.
• Strong experience with Data Science methodologies: model development, training, validation, and deployment, specifically around Machine Learning, AI, GenAI.
• Experience in data modeling, data cleaning, and feature engineering.
• Experience with data processing tools and ML platforms, especially Azure Machine Learning, Databricks (including the ML suite), or similar platforms.
• Strong understanding of data governance principles to ensure clean, compliant, and organized data structures.
• Familiar with the SCRUM-framework.
• Expertise in cloud programming languages (Python, SQL, JavaScript), and Python libraries such as TensorFlow, Pandas, PySpark, and Matplotlib.
• Experience with DevOps and MLOps environments, including automated model pipelines and CI/CD frameworks.
• Experience/knowledge of version control and collaboration tools such as Git and GitHub.
• Collaboration with key stakeholders such as data engineers, business analysts, and product owners throughout project lifecycles.
• Knowledge of testing strategies: unit testing, integration testing, acceptance testing, and functional testing.
• Affinity with mentoring, including the ability to coach junior team members and provide technical guidance to the team.