What we offer
- Interact with senior stakeholders on a regular basis, to drive their business towards impactful change.
- Become the go-to person for end-to-end data handling, management and analytics processes.
- Work with Data Engineers to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization.
- Become part of a fast-growing international and diverse team.
What you will do
- You own together with your team several of our Data Science solutions throughout the full life cycle (brainstorming, design, implementation, productization and maintenance).
- Analyze large datasets to identify trends, patterns, and insights, with a particular focus on energy consumption, production, and management.
- Develop, implement, and maintain predictive models and machine learning algorithms to optimize energy use and efficiency.
- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
- Create effective data visualizations to communicate findings and recommendations to both technical and non-technical stakeholders.
- Evaluate and improve model performance through validation techniques and hyperparameter tuning.
- Stay updated with the latest trends and advancements in data science and machine learning, especially as they pertain to the energy sector.
What you'll bring
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. A PhD is a plus.
- Minimum of 3 years of experience in a similar Data Scientist role.
- Strong programming skills in Python (R and Scala is a plus).
- Knowledge of predictive modeling techniques, time-series analysis, regression analysis, clustering, classification, and dimensionality reduction.
- Experience with machine learning tools and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Proficiency in SQL and database management systems (e.g. Databricks, Snowflake).
- Ability to manipulate and analyze large datasets using tools such as Pandas, NumPy, and other data analysis libraries.
- Experience creating visualizations using tools like Matplotlib, Tableau, or Power BI.
- Excellent communication skills and the ability to work collaboratively in a consultancy environment.
Preferred skills:
- Familiarity with cloud services, particularly Azure and Azure Functions.
- Knowledge and experience with dbt and GitHub.
- Experience deploying models in production environments.
- Knowledge of advanced machine learning techniques such as deep learning, NLP, and reinforcement learning.
- Familiarity with energy sector challenges and opportunities.
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