Prepare, clean, and validate datasets to ensure high‑quality inputs for analysis and modeling.
Perform exploratory data analysis (EDA) to identify trends, anomalies, and insights that guide solution design.
Develop and evaluate statistical and machine learning models for well‑defined business problems.
Implement, test, and validate models to ensure accuracy, robustness, and reproducibility.
Support deployment of analytics and ML solutions in collaboration with data engineers and software developers.
Monitor model performance and contribute to ongoing model maintenance and improvements.
Translate analytical findings into clear, actionable insights for technical and non‑technical stakeholders.
Document methods, assumptions, and results to support transparency and knowledge sharing.
Collaborate closely with cross‑functional teams and incorporate feedback from senior data scientists.
Contribute to a collaborative team environment and participate in knowledge-sharing activities.

Bachelor or Master degree in Computer Science, Statistics, Engineering, Mathematics, or a related field.
Strong English level, min. B2/C1
2–4 years of experience in data science, analytics, or a quantitative role.
Proven experience building, testing, and evaluating statistical or machine learning models.
Hands‑on work with real-world datasets, including cleaning, preprocessing, and feature engineering.
Experience collaborating with cross-functional teams (engineering, product, business).
Exposure to deploying analytics or ML solutions is a plus.
Industry experience in energy, engineering, or industrial settings is welcomed but not required.

Data Scientist

Key skills