The Data Science and Statistics programme responds to this demand by preparing highly skilled data analysts who can navigate the entire data analysis process—from data acquisition and preparation to model development and interpretation of results. It is open to students with backgrounds in statistics, mathematics, or computer science who wish to specialise in data-driven decision-making and predictive analytics.

The aim of this programme is to train specialists capable of performing complex data analyses and developing innovative analytical solutions for large and unstructured datasets. Unlike traditional statistics, modern data science addresses unique challenges related to the size, structure, and heterogeneity of data. This requires the integration of mathematical statistics with computer science, programing, and information technologies.

Students acquire the skills needed to program in R and Python, work with databases, and apply statistical modeling and forecasting techniques to solve real-world problems. The programme combines theoretical knowledge with practical applications, ensuring that graduates are well-prepared to analyse large-scale data, build predictive models, and assess model performance and quality.

Graduates will possess comprehensive knowledge of mathematical statistics, data science methodologies, and analytical software systems, enabling them to contribute effectively to both research and applied data projects.

Possible research areas include:

• Data analysis and modelling – works related to regression models, time series, missing data imputation, and indicator modelling

• Artificial intelligence and machine learning – research focusing on neural networks, classification methods, text and image recognition

• Economic and business applications – theses analysing real estate, transport, or service markets, price indices, and economic growth indicators

• Digital environment and online data sources – research examining advertising and tracking detection, user behaviour analysis online, and evaluation of data from virtual learning environments.

What will I be able to do?

Upon successful completion of the programme, graduates will be able to:

• Select appropriate mathematical models, parameter estimation methods, and quality assessment techniques for data analysis
• Prepare data for analysis, program in R and Python, and organise statistical research results for interpretation
• Develop mathematical and statistical models for both small- and large-scale data, estimate parameters, and evaluate model suitability
• Collaborate effectively in interdisciplinary and international research and professional teams.

What are my career opportunities?

• Data Analysts, Business Systems Analysts, or Risk Assessment Specialists
• Project Managers in business and government institutions in Lithuania and abroad
• Researchers or doctoral candidates in mathematics and related fields of the physical sciences.