● Worked with Power BI Desktop and Power BI Service. ● Connected to different data sources. ● Transformed data in Power Query. ● Created models in Power Pivot. ● Used DAX in reports.

● Used Python (pandas, seaborn, numpy, scipy, statsmodels, matplotlib, plotly, sqlalchemy, folium, IPython, os, phik, sklearn). ● Applied PostgreSQL (aggregation, grouping, JOIN, subqueries, CTE, window functions) ● Performed statistical analysis of data (Student's T-criterion, Mann-Whitney U-criterion, Fisher's Z-criterion). Calculated business indicators: cohort analysis, unit economics (LTV, CAC, ROI, ARPU, CR, Retention Rate). ● Prioritized hypotheses and analyzed A/B test results ● Told stories with data (Tableau, DataLens, Power Point) ● Got the basics of ML (EDA, regression, classification, clustering) Completed 11 learning projects (banks, computer games, real estate, scooter rentals, mobile apps). For example: ● Analyzed bank customers and identified segments of customers inclined to leave the bank. ● Analyzed the market of catering establishments in Moscow. ● Analyzed hypotheses and A/B test results for an online store. ● Analyzed the sales funnel and the results of an A/A/B test of a product sales application.

● Created a flow of client requests (website, advertising, SEO, e-mail). ● Created a system for processing requests (Google Docs, Telegram). ● Created visualizations and dashboards of changes in the value of investment portfolios: Tableau, Power BI, DataLens, Google Sheets, HighCharts. ● Implemented additional monetization of investment content. ● Reduced expenses on low-quality advertising sources by 99% due to unique GTM customization.