Summary of Degree Programme
Field of Studies
38.04.01 Economics
38.04.02 Management
Approved by
Academic Council Minutes No.10 of 26 October 2022
HSE University Educational Standard
Last Update
Minutes of St. Petersburg School of Economics and Management Council Meeting No. 8.3.2.4-08/2204-01 of 22 April 2024
Network Programme
No
Length of Studies, Mode of Studies, Credit Load
2 года 
Full-time, 120
Language of instruction
ENG
Instruction in English
Qualification upon graduation
Master
Double-degree Programme
No
Use of online learning
With online tools
Tracks
2026/2027 Academic year
Quantitative Business Analytics
Type:
Applied
Track Supervisor:
Karpinskaya, Emilia
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
- KER-1 Initiates, plans, and supports end‑to‑end projects for analytical solutions, managing project teams, risks, and organizational changes, while ensuring alignment with strategic business objectives.
- KER-2 Explains economic phenomena, processes, and behaviour of economic agents using concepts and explanatory models from economics and management.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Builds predictive models, tests statistical and economic hypotheses, and quantitatively evaluates alternative scenarios to justify management decisions under uncertainty, while clearly communicating the limitations and confidence intervals of forecasts.
- KER-5 Apply a broad range of analytical tools to key business functions such as finance, marketing, product management, operations, or HR, in order to diagnose inefficiencies, identify improvement opportunities, and enhance overall functional performance.
- KER-6 Develops evidence‑based recommendations and practical solutions for decision‑makers, synthesising analytical findings from models and diagnostic tools, and effectively communicates insights, trade‑offs, and implementation steps to stakeholders.
Description of the professional field:
- PC-1 Able to build predictive models, test hypotheses, and quantitatively evaluate alternatives to justify management decisions under conditions of uncertainty.
- PC-2 Able to apply analytical tools to key business functions in order to improve their efficiency.
- PC-3 Able to initiate, plan, and support projects for the implementation of analytical solutions, managing teams, risks, and organizational changes.
- Project manager / Product manager
- Data analyst
- Business analyst / BI analyst
- Marketing analyst / Product analyst
- HR analysts
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on conducting research in management and data analysis. The mentor support is provided through “Mentor's seminar”.
- The module “Internship” encompasses two types of internships – research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. The main courses equip students with a comprehensive skill set at the intersection of data science, economics, and management, enabling them to harness advanced analytical methods, machine learning, and econometric modelling for evidence‑based decision‑making across all business functions. It emphasises a hands‑on, project‑based approach to solving real‑world challenges, from marketing and finance to HR and product development, while fostering strategic thinking, digital transformation leadership, and entrepreneurial adaptability
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Quantitative Economics and Mathematical Methods
Type:
Applied
Track Supervisor:
Molchanov, Pavel S.
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
- KER-1 Initiates, plans, and supports end‑to‑end projects for analytical solutions, managing project teams, risks, and organizational changes, while ensuring alignment with strategic business objectives.
- KER-2 Explains economic phenomena, processes, and behaviour of economic agents using concepts and explanatory models from economics and management.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Builds predictive models and evaluates alternative scenarios under conditions of uncertainty, rigorously testing statistical and economic hypotheses while transparently communicating the limitations and confidence intervals of forecasts.
- KER-5 Demonstrates programming proficiency to solve applied problems in economics and finance, using relevant languages and tools to automate data processing and implement analytical models.
- KER-6 Develops evidence‑based recommendations and practical solutions for decision‑makers, synthesising analytical findings from models and diagnostic tools, and effectively communicates insights, trade‑offs, and implementation steps to stakeholders.
Description of the professional field:
- PC-1 Able to collect, “clean”, and analyse economic data, revealing underlying statistical and economic causal relationships.
-
- PC-2 Able to formulate an economic and econometric model of the studied problem/object of interest.
- PC-3 Able to use the available econometric and machine learning techniques to identify inefficiencies in customer or marketing business policies and propose a solution or an improvement.
- Project manager
- Data analyst
- Business analyst / BI analyst
- Economic analyst
- Researcher
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on conducting research in economics and data analysis. The mentor support is provided through “Mentor's seminar”.
- The module “Internship” encompasses two types of internships – research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. The main courses offer rigorous, research‑oriented training that fuses advanced economic theory with a comprehensive spectrum of contemporary empirical and quantitative methodologies, including causal inference, spatial and Bayesian econometrics, advanced statistical modelling, practical machine learning, and experimental design. Students develop the hands‑on technical skills to collect, process, and analyse complex data using modern programming tools, while applying decision analytics and modelling frameworks to address real‑world economic and market challenges.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
2025/2026 Academic year
People Analytics
Type:
Applied
Track Supervisor:
Volkova, Natalia
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
- KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Deal with various information systems and datasets for HR purposes.
- KER-5 Collect, analyse, and frame details about available resources in the labour market.
- KER-6 Manage employee motivation, engagement and workplace discipline.
Description of the professional field:
-
PC-1 Able to perform the full cycle of applied data analysis to develop evidence-based recommendations for strategic and tactical decision-making.
-
PC-2 Able to develop options for management decisions and justify their choice based on criteria for socio-economic efficiency.
-
PC-3 Able to develop reasonable HR system to reach organisational goals.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- HR analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on either business or HR field. The mentor support in People Analytics provides through “Mentor's Seminar”.
- The module “Internship” encompasses two types of internships – research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses involve gathering, analysing, and reporting HR data to measure the impact of a range of HR metrics on overall business performance and make decisions based on data.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Customer Analytics
Type:
Applied
Track Supervisor:
Pleshkova, Anastasiia
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
- KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Chooses tools, modern technical means, and information technologies for processing information in accordance with the assigned scientific and practical task in the field of management.
- KER-5 Takes decisions using CRM analytics using special methods for analysing network data and machine learning techniques.
- KER-6 Builds predictive models of various business outcomes using supervised learning methods for decision- making.
Description of the professional field:
-
PC-1 Able to perform the full cycle of applied data analysis to develop evidence-based recommendations for strategic and tactical decision-making.
-
PC-2 Able to develop options for management decisions and justify their choice based on criteria for socio-economic efficiency.
-
PC-3 Able to develop and justify a marketing strategy and a set of tactical measures aimed at achieving the organisation's business goals.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- Marketing analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on either business or HR field. The mentor support in Customer Analytics provides through “Mentor's Seminar”.
- The module “Internship” encompasses two types of internships – research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses involve gathering together, analysing, and reporting marketing data to make decision about customer behaviour and other marketing trends based on data.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Economic Data Analysis
Type:
Applied
Track Supervisor:
Molchanov, Pavel S.
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
-
KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Carries out a reasonable choice of data sources and methods for collecting and processing professional information, testing research hypotheses and the reliability of the data obtained, calculates analytical indicators.
- KER-5 Proficient in programming to solve problems in the field of economics and finance.
- KER-6 Able to collect, analyse and process statistical data, information, scientific and analytical materials necessary to solve economic problems.
Description of the professional field:
-
PC-1 Able to collect, “clean”, and analyse economic data, revealing underlying statistical and economic causal relationships.
- PC-2 Able to formulate an economic and econometric model of the studied problem/object of interest.
- PC-3 Able to use the available econometric and machine learning techniques to identify inefficiencies in customer or marketing business policies and propose a solution or an improvement.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- Economic analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on conducting research in economics and data analysis. The mentor support is provided through “Mentor's seminar”.
- The module “Internship” encompasses two types of internships – research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses teach fundamental economic knowledge (microeconomics), econometrics and machine learning. Consequently, will know how to collect, clean the data, formulate a theoretical model, and use the state-of-the-art statistical methods to provide quantitatively sound solutions to a business-problem.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
2024/2025 Academic year
People Analytics
Type:
Applied
Track Supervisor:
Volkova, Natalia
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
-
KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Deal with various information systems and datasets for HR purposes.
- KER-5 Collect, analyse, and frame details about available resources in the labour market.
- KER-6 Manage employee motivation, engagement and workplace discipline.
Description of the professional field:
- PC-1 Able to perform the full cycle of applied data analysis to develop evidence-based recommendations for strategic and tactical decision-making.
- PC-2 Able to develop options for management decisions and justify their choice based on criteria for socio-economic efficiency.
- PC-3 Able to develop reasonable HR system to reach organisational goals.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- HR analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on either business or HR field. The mentor support in People Analytics provides through “Mentor's Seminar”.
- The module “Internship” encompasses three types of internships – professional, research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses involve gathering, analysing, and reporting HR data to measure the impact of a range of HR metrics on overall business performance and make decisions based on data.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Customer Analytics
Type:
Applied
Track Supervisor:
Pleshkova, Anastasiia
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
-
KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Chooses tools, modern technical means, and information technologies for processing information in accordance with the assigned scientific and practical task in the field of management.
- KER-5 Takes decisions using CRM analytics using special methods for analysing network data and machine learning techniques.
- KER-6 Builds predictive models of various business outcomes using supervised learning methods for decision-making.
Description of the professional field:
- PC-1 Able to perform the full cycle of applied data analysis to develop evidence-based recommendations for strategic and tactical decision-making.
- PC-2 Able to develop options for management decisions and justify their choice based on criteria for socio-economic efficiency.
- PC-3 Able to develop and justify a marketing strategy and a set of tactical measures aimed at achieving the organisation's business goals.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- Marketing analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on either business or HR field. The mentor support in Customer Analytics provides through “Mentor's Seminar”.
- The module “Internship” encompasses three types of internships – professional, research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses involve gathering together, analysing, and reporting marketing data to make decision about customer behaviour and other marketing trends based on data.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Economic Data Analysis
Type:
Applied
Track Supervisor:
Molchanov, Pavel S.
Language of instruction:
English
Use of online learning:
With online tools
Qualification upon graduation:
Master
Key learning outcomes:
-
KER-1 Organises work of the project team to solve analytical problems, build forecasts and scenarios, and develop decisions regarding optimal policies based on evidence-based principles.
- KER-2 Explains economic phenomena, processes and behaviour of economic agents based on concepts and explanatory models in economics and related sciences, identifies significant problems and develops ways to solve them, provides recommendations to decision makers.
- KER-3 Makes a reasonable choice of methods and, where necessary, software tools for collecting and processing professional information, testing research hypotheses and reliability of the obtained data.
- KER-4 Carries out a reasonable choice of data sources and methods for collecting and processing professional information, testing research hypotheses and the reliability of the data obtained, calculates analytical indicators.
- KER-5 Proficient in programming to solve problems in the field of economics and finance.
- KER-6 Able to collect, analyse and process statistical data, information, scientific and analytical materials necessary to solve economic problems.
Description of the professional field:
-
PC-1 Able to collect, “clean”, and analyse economic data, revealing underlying statistical and economic causal relationships.
- PC-2 Able to formulate an economic and econometric model of the studied problem/object of interest.
- PC-3 Able to use the available econometric and machine learning techniques to identify inefficiencies in customer or marketing business policies and propose a solution or an improvement.
Graduates of the programme can pursue careers in data analytics and machine learning in such roles as:
- Project manager
- Data analyst
- Business analyst / BI analyst
- Economic analyst
Description of educational modules:
- The module “Key seminars” consists of various activities with focus on project and research skills via Research seminar. Research seminars focus on conducting research in economics and data analysis. The mentor support is provided through “Mentorship seminar”.
- The module “Internship” encompasses three types of internships – professional, research and project. Master thesis is an essential part of research internship.
- The module “Major” includes courses that serve for the development of professional, research and data skills. As such, students can gain knowledge and competencies in Economics, Marketing and Human Resource management. The main courses teach fundamental economic knowledge (microeconomics), econometrics and machine learning. Consequently, will know how to collect, clean the data, formulate a theoretical model, and use the state-of-the-art statistical methods to provide quantitatively sound solutions to a business-problem.
- The module “MagoLego” provides students with additional knowledge according to their preferences and supports students in strengthening their professional trajectory.
Competitive Advantages
- Avant-garde programme in management and business-economics taught in English.
- Emphasis on business strategies and economics for emerging markets.
- Emerging markets and their specific traits when it comes to strategic management, economics and data-driven decisions.
- The development of the data skills to interpret and analyze complex phenomena in the fields of marketing, economics, strategy, and human resources, in close cooperation with companies.
- Advanced skills connected with machine learning techniques for extracting predictive patterns and models from digital data.
- Opportunity to choose an applied track or a research-oriented track followed up by PhD study abroad or under supervision of HSE international research centers.
- Cross-Functional Competencies:The programme’s courses cover a wide range of competencies in strategic management and business economics, as well as in big data analytics, quantitative methods, and machine learning.
- An Applied Curriculum:The curriculum is oriented around the knowledge and skills most sought-after among employers in real workplaces.
- Experienced Teaching Staff: Courses are taught by academic and business experts
Programme Modules
Options for Students with Disabilities
This degree programme of HSE University is adapted for students with special educational needs (SEN) and disabilities. Special assistive technology and teaching aids are used for collective and individual learning of students with SEN and disabilities. The specific adaptive features of the programme are listed in each subject's full syllabus and are available to students through the online Learning Management System.
Programme Documentation
All documents of the degree programme are stored electronically on this website. Curricula, calendar plans, and syllabi are developed and approved electronically in corporate information systems. Their current versions are automatically published on the website of the degree programme. Up-to-date teaching and learning guides, assessment tools, and other relevant documents are stored on the website of the degree programme in accordance with the local regulatory acts of HSE University.
I hereby confirm that the degree programme documents posted on this website are fully up-to-date.
Vice Rector Sergey Yu. Roshchin
Summary of Degree Programme 'Data Analytics for Business and Economics'
