Professional knowledge
At the concept level:
1. Economic development; statistical indicators for specialisation.
2. Industry-specific terms, operating principles and characteristics.
At the level of understanding:
1. Mathematical theory; statistical theory.
2. Mathematical theory; statistical theory.
3. EU General Data Protection Regulation; copyright.
4. Communication methods; data protection; copyright.
5. Data protection; database design and construction.
6. Database design and construction.
7. Theory of economics.
8. Data protection.
At the level of use:
1. Mathematical methods; statistical methods.
2. At least one programming language; specialised mathematical and statistical software.
3. Mathematical methods; statistical methods; model building and implementation.
4. Mathematical methods; statistical methods; model building and implementation; specialised mathematical and statistical software.
5. Research framework, types of research and data collection methods.
6. Sample surveys and generalisation of results; research framework.
7. Mathematical and statistical methods; sample surveys; use of databases; specialised mathematical and statistical software.
8. Mathematical and statistical methods; specialised data-processing software.
9. Mathematical and statistical methods, specialised mathematical and statistical software.
10. Presentation skills; communication technologies; mathematical modelling.
11. Professional ethics; mathematical and statistical methods; specialised mathematical and statistical software.
General knowledge
At the concept level:
1. Information technology legislation.
At the level of understanding:
1. Labour law, copyright, confidentiality of information, data protection.
2. Regulatory enactments on occupational health and safety, electrical safety, civil protection and environmental protection; basic ergonomic requirements; human health risk factors.
3. Information technology opportunities and potential risks; electronic information security.
4. Principles of fostering cooperation; team building.
5. Professional career development and its importance.
At the level of use:
1. Legislation relevant to the specialty.
2. Preventive measures for assessing risk factors in the work environment; requirements of legislation governing civil and environmental protection; emergency response; first aid.
3. Computer security programs; information systems security.
4. Effective communication and cooperation techniques; general and professional ethics.
5. National language; sufficient vocabulary in at least one foreign language; professional terminology; scientific style.
6. Principles of self-assessment.
7. Planning one’s studies, career and work.

Professional skills and attitudes
1. Mathematically formulate the problem and the problem statement.
2. Choose appropriate mathematical models for given statistical data.
3. Identify and evaluate model assumptions.
4. Justify the chosen model.
5. Implement the chosen statistical method with a specific information technology tool.
6. Work with large amounts of information.
7. Keep up to date with developments in information technology.
8. Develop a methodology for data analysis.
9. Report on results obtained.
10. Prepare documentation.
11. Improve existing statistical methods and mathematical models using the latest information technologies.
12. Adapt and apply mathematical models to solve problems in one’s field of specialisation.
13. Identify the aim and objectives of a study.
14. Set out research hypotheses.
15. Choose methods to test hypotheses.
16. Develop a data extraction methodology.
17. Design and conduct data extraction for different types of research framework (sample survey, experimental data, data from secondary data sources, etc.).
18. Extract qualitative statistical data from a variety of information sources.
19. Work with official statistics.
20. Compile data using specialised mathematical and statistical software.
21. Use and process databases containing statistical information.
22. Use up-to-date technologies for acquiring, processing and organising information.
23. Assess data quality.
24. Process data using specialised mathematical and statistical software.
25. Perform descriptive statistics.
26. Build and analyse mathematical, statistical and data mining models.
27. Use statistical tests to test hypotheses.
28. Visualise data, models and results.
29. Present the results of data analysis according to the specifics of the task and industry requirements.
30. Make recommendations for decision-making based on the results.
31. Be familiar with industry terminology and methods.
32. Advise on the selection and use of appropriate statistical methods for the purpose of a study.
33. Understand the structure and operation of a company, and know the main statistical models and methods used in a company.
34. Maintain professional neutrality and objectivity of a statistician by explaining the meaning and results of statistical data in an objective, professional and transparent manner, respecting scientific independence and treating all clients equally.
General skills and attitudes
1. Comply with the law.
2. Comply with sector-specific laws and regulations.
3. Organise one’s workplace and work in accordance with occupational health and safety and safety requirements.
4. Comply with the requirements of occupational health and safety, civil protection and environmental protection laws and regulations.
5. Comply with fire safety rules.
6. Act as required in an emergency.
7. Provide first aid.
8. Use information technology tools and services.
9. Communicate in networks using the internet.
10. Ensure storage of electronic documents and data.
11. Respect IT security and personal data protection requirements.
12. Work as part of a team, recognising one’s responsibility for the overall work.
13. Adhere to general and professional ethics.
14. Communicate in the national language.
15. Use professional terminology in the national language and at least one foreign language.
16. Respect the culture of language.
17. Know how to find information in a foreign language(s).
18. Communicate orally and in writing in a variety of professional situations.
19. Assess one’s professional experience and career possibilities.
20. Systematically acquire new knowledge and experience.
21. Follow industry news.

Professional competences
1. Ability to find the most appropriate mathematical models for given statistical data.
2. Ability to evaluate model assumptions.
3. Ability to decide on the best model.
4. Ability to implement statistical methods with information technology tools.
5. Ability to independently learn new statistical computer programmes.
6. Ability to select the most appropriate data processing methods.
7. Ability to use scientifically sound data processing methods.
8. Ability to develop and scientifically justify data analysis methods.
9. Ability to adapt the latest scientific findings to one’s area of specialisation.
10. Ability to work with a variety of data extraction tools.
11. Ability to design a research plan.
12. Ability to design statistical experiments in a scientifically sound way.
13. Ability to obtain and evaluate the information and data needed to carry out one’s work.
14. Ability to compile data in different formats.
15. Ability to independently maintain and update company databases containing general statistical information.
16. Ability to process data using specialised mathematical and statistical software.
17. Ability to perform data explication.
18. Ability to analyse results using mathematical and statistical methods.
19. Ability to draw valid conclusions based on the results of data processing.
20. Ability to build scientifically sound models and assess their reliability.
21. Ability to explain the results of data analysis to specialists in the relevant field, using terminology appropriate to the field.
22. Ability to make recommendations for decision-making based on the results.
23. Ability to communicate and interact with clients in a professional and ethical manner.
24. Ability to advise on statistical methods and models.
25. Ability to propose modifications, innovative solutions and improvements to existing statistical methods.
26. Ability to explain the statistical results obtained in a clear and illustrative manner, making them understandable and accessible to those seeking advice.
General competences
1. Ability to carry out work tasks in compliance with the legislation and confidentiality requirements of the profession.
2. Ability to carry out work tasks in accordance with the requirements laid down in the legislation.
3. Ability to handle emergencies and provide first aid.
4. Ability to carry out work tasks in compliance with statutory occupational health and safety and environmental protection requirements.
5. Ability to use information and communication technologies to carry out work tasks.
6. Ability to continuously develop skills in the use of the latest information technologies.
7. Ability to work effectively as part of a team.
8. Ability to adhere to general and professional ethics.
9. Ability to communicate freely and use professional terminology in the national language and at least one foreign language.
10. Ability to obtain information needed to carry out the tasks in the national language and at least one foreign language.
11. Ability to plan and make decisions for own career.