Junior Data Scientist (f/m/n)

InPost Group is an innovative European out of home deliveries company operating across several countries with a network of intelligent lockers. It is publicly traded with a market capitalization of about $5 billion as of March 2023 and employs over 10,000 people worldwide. InPost Group is one of the largest out of home delivery providers in Europe, focusing on sustainable and efficient delivery solutions.

• Higher education in progress or completed (Bachelor’s or Master’s) in computer science, statistics, mathematics, physics, econometrics, or related field
• Around a year of commercial or internship experience in data analysis or data science, or strong academic/research/competition record
• Good knowledge of Python (Pandas, NumPy, Scikit-learn) and practical SQL skills
• Solid grounding in data cleaning, wrangling, exploratory data analysis, and basic statistics
• Familiarity with core ML methodologies (regression, classification), evaluation metrics, and cross-validation
• Ability to visualize and communicate insights clearly (e.g., Matplotlib, Plotly)
• English language proficiency at B2 level or higher
• Proficiency in LLM-Agentic technology in software development (Claude Code, Cursor, OpenAI Codex, etc.)

Nice to have:

• Strong track record in data science/ML competitions, olympiads, or hackathons
• Documented academic or personal projects in data analysis or machine learning
• Exposure to time series or forecasting methods (ARIMA, gradient boosting, modern approaches)
• Familiarity with PySpark or other big-data tools
• Basic understanding of cloud platforms (AWS, GCP, Azure) and data pipelines (Airflow, dbt)
• Experience building dashboards and reports (Streamlit, Dash, Power BI)
• Exposure to containerization and experiment tracking (Docker, MLflow)
• Reproducible-workflow habits: notebooks, Git, clean code, and clear documentation
• Results-oriented, independent, analytical, quality-minded, good planning, and teamwork skills

• Run end-to-end forecasting analyses on real business problems, including data preparation, feature engineering, modeling, and delivering actionable recommendations
• Build and evaluate time series and machine learning forecasting models with rigorous testing and iterative improvement
• Write clean, well-structured code and participate in code reviews
• Take ownership of tasks by estimating work, communicating progress, and flagging issues early
• Support the full lifecycle of forecasting products, including model maintenance and handovers
• Continuously deepen technical foundations and forecasting expertise through collaboration and on-the-job learning