**Company Description
InPost Group** is an innovative European out of home deliveries company, revolutionizing the way parcels are delivered to customers. With operations across several countries, our network of intelligent lockers provides customers with a fast, convenient, and secure delivery option. InPost Group is a publicly traded company, with a market capitalization of about $5 billion as of March 2023. With over 10,000 people worldwide, InPost Group is one of the largest out of home delivery providers in Europe , committed to providing sustainable and efficient delivery solutions to meet the evolving needs of customers in today's rapidly changing landscape.
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.
Qualifications
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.
Required:
- 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.
Additional Information
- Remote role across Poland.
- 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