The management of the “Data Analytics for Business and Economics” programme is delighted to share the competence profile of a graduate!

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Together with the Academic Council of the programme, chaired by A.S. Poperlyukov, CEO of Gazpromneft - Digital Solutions, and the academic supervisors of the tracks (N.V. Volkova, A.Y. Pleshkova, P.S. Molchanov), 6 key competencies were formed, which will be developed in the process of studying at the “Data Analytics for Business and Economics” programme. During the preparation of the graduate profile, the members of the Academic Council got acquainted with the content of the program and the specifics of its implementation, in addition, one of the main tasks was to form a strategy for the development of the educational program and increase its attractiveness for both applicants and employers.  As a result, the concept of the "Graduate Profile" and 6 competencies that the program will help applicants develop were developed:

For each competency, there are a number of disciplines (from 4 to 8) that will help applicants, students, and then graduates to achieve development in the given areas. More details about the conditions of admission can be found on the web page or you may ask your question in the telegram group of the program.

Let's talk a little bit about each of the 3 tracks that are available to our students.

1. People analytics

For those who are interested in developing a career in human resource management, the People analytics track is suitable (the track mentor is Volkova N.V.). In today's world, the amount of data that companies collect is growing exponentially, so it is important for every organization to have specialists in the team who can analyze it and use it to make management decisions. In addition, widespread digitalization, high turbulence and uncertainty, as well as a change in traditional business models have led to a radical change in HR operational processes, in the implementation of which data analytics plays a crucial role. It's no wonder that HR services need more than ever employees who can handle large amounts of information. If you open job sites, for example, HH and start looking for vacancies in the field of data analytics in HR or HR management, the number of such offers at the moment is in the hundreds in large cities. Thus, the demand for this area in the labor market is obvious.

Studying on the People Analytics track of the Master's programme “Data Analytics for Business and Economics” will help our graduates not only master the necessary skills that will allow them to effectively analyze data and make informed decisions, but also develop cross-functional competencies in the field of economics and marketing. For these purposes, during the first year of study, all subjects for students of the three tracks (marketing, economics and HR) are the same, and specialization begins in the second year. It is important to note that classes are held either on Saturdays or in the evening from 6 p.m.

As part of the program, students will learn how to work with various tools and technologies that are used in data analysis, such as SQL, Python, R, Excel, and BI platforms for data visualization. These tools will be considered in the context of core human resource management processes. Business practitioners are actively involved in conducting specialized disciplines on the track. As a result of mastering data analytics skills, our graduates will be able to:

• Optimize business processes in the field of human resource management and increase the efficiency of the company
• Create and implement data-driven strategies for the development of the organization and department
• Improve employee engagement and employee experience
• Optimize personnel costs based on data and artificial intelligence

2. Customer analytics

As part of the Customer analytics track (track mentor A.Y. Pleshkova), students will gain valuable knowledge that will help answer the following questions:

• How to optimize marketing costs across different channels?
• How to predict and prevent customer churn?
• Which customers generate the most revenue?
• Which geographic areas should you target?
• Which customers are likely to return in the next 3 months?
• What products can be offered to each individual customer additionally?

Customer analytics involves collecting and analyzing customer data to identify patterns in customer behavior. The track will look at ways to implement consumer analytics data to make better business decisions that will improve the customer experience and retention rates. The track disciplines will also help you figure out how to track various metrics throughout the customer journey, such as the number of registrations and leads, the level of adoption of new features, and the churn rate.

The more you know about your users, the more you'll be able to tailor your product and marketing policies to increase revenue. Customer analytics provides managers with information that can be used in a variety of ways:

• Improve retention: Identify churn indicators, address problem areas in the customer journey, learn which milestones lead to increased customer loyalty, and how to motivate other consumers to achieve these metrics.
• Create better experiences: Understanding how consumers use communication platforms will help prioritize and personalize the features of those engagement platforms.
• Improve the effectiveness of marketing communications: By analyzing consumer data, you can identify which types of consumers generate the most revenue or have the longest retention rates, and then make smarter marketing decisions based on design and text that provide the highest response rates.

Students of the Customer analytics track successfully implement projects that are also related to analytics, for example:

• “Optimization of marketing strategies in the field of ticketing systems”
• “Analytics and Consulting in Media Marketing”
• “Promotion of the HSE “Data Analytics for Business and Economics” programme as part of the following events: Open Day and Winter School 2024"
• "Creating a Map of Research Methods" "Creating a Dashboard on the Innovative Predisposition of Generation Z" 
• "Developing the omnichannel of Lenta's customers through e-mail communications"

Each academic discipline in the courses of this track is devoted to solving a practical problem (A/B testing, Uplift modeling, modeling the impact of advertising on sales, shopping cart analysis, etc.). As a result, even graduates of the program who do not have formal practical experience accumulate materials for their own portfolio and will be able to easily convince the employer of their value.

3. Economic data analysis

As part of the Economic data analysis track (track mentor P.S. Molchanov), students will gain skills in machine learning, microeconometrics, and quantitative models. The track program will allow you to extract valuable information from complex data sets and form recommendations for business or the state. The economics track can be characterized by the following three main subjects, each of which lasts for two years:

1. Econometrics – summarizes information using a model, using the methods of mathematics and statistics. At the same time, a great emphasis is placed on the interpretation and explanation of the mechanism of the influence of factors on the dependent variable. In the process of classes, the student will understand what and how econometrics studies, and work out the knowledge gained on examples from life. Students will learn how to build relevant models based on real data and draw informed conclusions from the results.
2. Machine learning is a set of methods that allow you to study patterns based on an accumulated database of past observations. The focus is on the predictive ability of the model and working with very large data sets. This course is taught by a practitioner from the industry. You'll learn how to use examples to apply machine learning to classification tasks, predict expected loan profitability, and solve other problems that often arise when working as an analyst in banking or large companies.
3. Microeconomics – provides a theoretical framework for economic thinking and is a mandatory course for any economist. You will learn how to model consumer behavior, analyze competition, analyze demand for goods and develop an optimal pricing policy, model relationships between market players (game theory), etc.

Economics students often work closely with researchers from two research centers located in the same building: (i) the Center for Market Studies and Spatial Economics, and (ii) the Center for Game Theory and Decision Making. Both centers provide a unique opportunity to conduct their academic research under the guidance of scholars published in the best international journals. Often, our students give seminars for undergraduate studies and continue their academic careers in graduate school.

What can graduates of the Economic data analysis track do??

• Data Analyst

Transforms data, analyzes it using statistical methods, visualizes the results of their analysis, and makes data-driven decisions;

• Econometrician

Develops and improves models for forecasting the economy and economic processes;

• Risk Manager in the Financial Sector

Assesses and manages risks in the insurance and finance industry;

• Economic Consultant

Develops expert opinion on economic and political issues for enterprises, government agencies and organizations.

Also, within the framework of all tracks, it is possible to develop in an academic trajectory - to continue your career path within the walls of HSE University and become a PhD student, and then a teacher. We look forward to meeting you and wish you good luck!

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