Junior Data Scientist (f/m/n)
Role details
Job location
Tech stack
Job description
You'll join the Forecasting Domain within our Data & AI division as a Junior Data Scientist.
Our team predicts parcel volumes and operational demand across multiple European markets - forecasts that drive planning, capacity and decisions all the way up to C-level. This is a role built for someone at the start of their career: you'll learn directly from experienced data scientists, contribute to real forecasting models from day one, and grow along a clear path from Junior toward Senior and beyond. We care more about how you think than how many years you've worked.
Tech stack: Python (Pandas, NumPy, Scikit-learn), SQL & data warehouses, PySpark & distributed processing, Databricks, Cloud platforms (Azure / GCP / AWS).
Working under the guidance of senior team members, you will:
- Run end-to-end forecasting analyses on real business problems - from data preparation and feature engineering through to modelling and turning results into clear, actionable recommendations
- Build and evaluate time series and machine learning forecasting models, validating them through rigorous testing and iterative improvement
- Write clean, well-structured code and take part in code reviews to keep our standards high and share knowledge
- Take ownership of your tasks: estimate your work, communicate progress, and flag issues early to deliver on time
- Support the full lifecycle of our forecasting products, helping maintain models in production and contributing to handovers
- Keep learning - deepening your technical foundations and forecasting expertise through on-the-job work and close collaboration with the team
You'll work day-to-day with data scientists, product leads, ML engineers, data engineers and business stakeholders, so clear communication matters as much as clean code., * Access to e-learning platforms- eTutor, GoodHabitz, Data Camp, and more.
- A wide range of benefits, including the MultiSport+ card, private healthcare, and group insurance, is available on the Worksmile platform.
- External and internal growth opportunities - conferences, trainings, workshops.
- Chances to broaden your skill set and acquire new competencies through daily work, challenging projects, and training activities.
- B2B type of contract
Requirements
We don't expect you to tick every box. We're looking for a sharp analytical mind, genuine curiosity, and a strong quantitative foundation - the commercial experience is something you'll build with us., * Higher education in progress or completed (Bachelor's or Master's) in computer science, statistics, mathematics, physics, econometrics or a related field
- Around a year of first commercial / internship experience in data analysis or data science - or an equally strong record of documented academic, research or competition participation
- Good knowledge of Python for data workflows (Pandas, NumPy, Scikit-learn)
- Practical SQL skills for querying relational databases
- Solid grounding in data cleaning, wrangling and exploratory data analysis (EDA), and a good understanding of basic statistics
- Familiarity with core ML methodologies (regression, classification), including evaluation metrics and cross-validation
- Ability to visualise and communicate insights clearly (e.g. Matplotlib, Plotly), with focus on storytelling and clarity
- English at B2 level or higher
- Proficiency in the use of LLM-Agentic technology in software development: Claude Code, Cursor, OpenAI Codex, etc.
You'll stand out if you have:
- A strong track record in data science / ML competitions (Kaggle and similar), olympiads or hackathons
- Documented academic or personal projects in data analysis or machine learning - a thesis, research, publications or a solid github portfolio
- Exposure to time series or forecasting methods (e.g. ARIMA / classical statistical models, gradient boosting, or modern forecasting approaches)
- Familiarity with PySpark or other big-data tools
- A basic understanding of cloud platforms (e.g. AWS, GCP, Azure) and simple data pipelines (Airflow, dbt)
- Experience building dashboards and reports (Streamlit, Dash, Power BI)
- Exposure to containerisation and experiment tracking (Docker, MLflow)
- Reproducible-workflow habits: notebooks, Git, clean code and clear documentation
We're looking for someone who is results-oriented, independent, analytical and quality-minded, who plans their work well and enjoys working as part of a team.