Experience

Лига Цифровой Экономики

• Russian Federation
• Information Technology & Services
• 500 - 600 Employee

• Data Analyst

  • May 2022 - Present

  Project for a major oil company Gazprom.The structure of the company consists of several subsidiaries, which are responsible for the production of oil and gas in their respective fields. The company has both IT products for subsidiaries and general ones for the company.Business wants to know how things are in production, so my tasks include finding the necessary data in the company's IT systems and transforming this data for visualization in dashboards using the SQL. This includes collecting and analyzing requirements from the business, working with colleagues from source systems to determine the availability of data, participating in the formation of technical specifications for the integration of the source system with the data warehouse, analyzing and transforming data into the view required for visualization in dashboards.Often the data is available only in the form of excel reports. Such reports often contain a large number of non-informative lines, special characters, tables in a wide format and names that are incomparable with other systems. In such cases, I use python to bring the data into a form suitable for RDBMS and continue my analysis using the SQL. The end product of the work is a data mart that allows company to build visualizations with it and make data driven decisions. Show less

• Data Analyst

  • Aug 2021 - May 2022

  Project for one of the largest telecommunications companies, Rostelecom. The end result was accounts receivable data mart.The task was quite difficult, since Rostelecom united 15 smaller telecom companies and their IT architecture often differed from each other. These companies used different algorithms for calculating traffic, debts and accounting for customers. Therefore, the integration of all source systems was not trivial.My main task was to analyze the data received from the source systems. Writing SQL scripts that transform the received data into the form required by the customer. Writing tests that ensured the quality of the transformation. Create documentation describing data transformation, data loading, and tests performed. Demonstration of the work done to the customer.I found that some parts of the tasks are pretty repetitive and can be automated with python. This included creating issues in JIRA using their API, generating repetitive pieces of documentation and tests.But sometimes there were situations when the data from the source systems did not allow meeting the business requirements. Then it was necessary to identify the problem to the business and develop new requirements. Show less



Лига Цифровой Экономики

• Russian Federation
• Information Technology & Services
• 500 - 600 Employee

• Junior Data Analyst

  • May 2020 - Jun 2021

  Project for a large telecommunication company Megafon. The company has several websites, the main one having over 10 million hits every month. The company is interested in assessing changes in the design of the site, the impact of changing the order of goods and tariff plans. As part of a team of analysts working closely with marketers and a team of engineers responsible for implementing changes to the website and collecting information, I participated in the development of conceptual metrics and their technical definitions. Conducted A/B and A/A testing, selected separation units, evaluated dataset variability using parametric and non-parametric methods. Estimate the amount of data needed to collect based on the variability of the data and the size of the effect that would be significant to the business. Often there were problems with the collected data, and I found out from the engineers what could go wrong. Presented data-driven findings and recommendations to the client. A small project for the department of Information Technologies of the City of Moscow. The department needed information on morbidity, mortality and recovery from covid for all countries. Information was collected through web scraping from open official sources. Further, with the help of this information, visualizations and forcasts for the department were made. By the time I joined the project, the predictive machine learning models had already been written and the process of collecting data from open sources for visualizations was in place. The problem was that the structure of open sources often changed and python scripts needed to be adapted. My task was that the required information was available every day. If this did not happen, it was necessary to correct the python scripts to obtain this information. Show less



Freelance

• Web Developer

  • Dec 2018 - Dec 2019



Financial broker

• Cook Islands
• Financial Services
• 1 - 100 Employee

• Web Developer

  • Oct 2016 - Jul 2017