Data Scientist

Job Purpose

As a Data Scientist, you will work on clearly defined analytical use cases, preparing data, building and validating models, and contributing to their deployment in production. Collaborating with senior data scientists, engineers, and business stakeholders, you'll help translate data into actionable insights, drive efficiency improvements, and continuously build your technical and domain expertise.

Job Description

•    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.

You are meant for this job if:

•    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.

Technical Skills

•    Strong programming skills in Python (and/or R) and working knowledge of SQL.
•    Familiarity with key libraries such as pandas, numpy, scikit‑learn.
•    Ability to perform EDA, model evaluation, and validation.
•    Basic experience with data visualization tools (e.g., matplotlib, seaborn, Power BI, Tableau).
•    Experience with Git and collaborative development workflows.
•    Exposure to cloud platforms, containers, or MLOps tools is an advantage.

Soft Skills

•    Excellent communication skills, able to explain complex concepts clearly.
•    Collaborative mindset and ability to work with diverse technical and business teams.
•    Strong analytical thinking and a structured approach to problem-solving.
•    Curiosity and commitment to continuous learning.

Please submit your CV in English.