Data Science Internship — Remote, Mentorship & Real Projects

Accenture; Kraków; Hybrid; PLN 17,000 - 23,000; Full time

Job summary

Accenture Kraków is seeking a Data Science Intern to join our team and help build data-driven solutions using statistics, machine learning and AI technologies.

You will work across the data science lifecycle—from data preparation and exploration, through modelling and evaluation, to deploying and monitoring models in production. Active student status and at least 30 hours per week are required, with opportunities to collaborate with international teams.

Qualifications

• Active student status and availability of at least 30 hours per week.
• Pursuing a degree in Data Science, Computer Science, Mathematics, Statistics, Econometrics, or a related quantitative field.
• Strong understanding of statistics, probability theory, and fundamental machine learning concepts.
• Proficiency with Python and libraries: Pandas, NumPy, scikit-learn.
• Good command of English and Polish communication skills.

Responsibilities

• Explore, clean and analyze datasets to identify patterns and insights.
• Apply statistical and probabilistic methods to real-world problems.
• Develop, train and evaluate ML and statistical models.
• Perform feature engineering and experiment with modelling approaches.
• Work on predictive modelling and time series forecasting problems.
• Evaluate model performance and analyze prediction errors.
• Support the deployment and monitoring of models in production.
• Contribute to experiments with modern AI and Generative AI solutions.
• Document your work and communicate findings to the team.
• Collaborate with Data Scientists, ML Engineers and business stakeholders.

Skills

Python programming

Statistics

Probability theory

Machine learning concepts

Communication skills

English and Polish

Education

Quantitative degree program

Tools

Pandas

NumPy

scikit-learn

Job description

Accenture Kraków is seeking a Data Science Intern to join our team and help build data-driven solutions using statistics, machine learning and AI technologies.

You will work across the data science lifecycle—from data preparation and exploration, through modelling and evaluation, to deploying and monitoring models in production. Active student status and at least 30 hours per week are required, with opportunities to collaborate with international teams.