Position: Data Analyst
Category: Data Analyst
Experience: 1.5 years | English: upper

I became interested in data analytics during the pandemic quarantine and completed the Yandex.Practicum course with a degree in Data Analyst. During the course of training, I made a pet-project for the analysis of free text responses using the TextHero natural language processing library. This is an internal study conducted by the company's HRs to identify employee attitudes towards remote work. The result of the analysis was a public study with comments from top officials of the company.

After completing the course, I analyzed all the data available to me at my current job: conversions from the site, conversions from mailings.

Continuing self-education, in the spring of 2021, I completed an internship at the Institute of Business Intelligence, during the course I set up sales reporting dashboard in Power BI for the CEO, set up monthly reporting dashboard for the marketing department.

After the internship I've coded automositation of the NPS prosess.

My hobby is contemporary art, I am a resident of the self-organized art group APXIV.
Busines Analyst, Sibur, Moscow
Automatization ETL (Python)
Calculating Metrics for Visualization (Python + Tableau)
Building Tableau dashboards to visualize core business KPIs (Tableau Server)
Dashboards optimization
Scripting (Python) and automatization (Windows scheduler) weekly productivity reports to send via Outlook 

Senior Brand Manager, BDO, Moscow
Collecting, processing and analyzing customer feedback on the results of each project: NPS index (Python + Power BI)
Automation of mailing with a request and results of feedback from a client (Python)
Development and support of reporting on requests from the site, social networks, mailings, the work of the marketing department in Power BI
Development and support of reporting with a forecast of sales for DG in Power BI
Analysis of RFP from the site, counting conversions, funnels
Data journalism

Data Analytic, Yandex.Practicum, learning experience
Predicting the likelihood of churn for fitness centers: based on data about visitors to a network of fitness centers, predict the probability of churn for each client in the next month and form user portraits using clustering. Stack: Python, Pandas, StandardScaler, LogisticRegression, RandomForestClassifier, KMeans. Result: A list of signs that most affect the churn, a portrait of the chipper, conclusions and recommendations for improving the quality of work with clients. 

Creating a dashboard based on custom events for a news aggregator: using Yandex.Zen data, build a dashboard with metrics of user interaction with article cards. Stack: PostgreSQL, Python, SQLAlchemy, Tableau dash, Numpy, Scipy, dashboard building, product metrics. Result: dashboard  and presentation.

Analysis of user behavior in a mobile application: based on data on the use of a mobile application for selling food, analyze the sales funnel, also evaluate the results of A / A / B testing. Stack: A / B testing, Python, Pandas, Plotly, Seaborn, data visualization, statistical hypothesis testing, product metrics, event analytics. Result: no statistically significant differences were found between the A and B groups, which means that the hypothesis that changing the font affects the conversion metrics was not confirmed.
Мне нравится визуализация и storytelling данных. Люблю автоматизировать процессы :)