Position: Junior Data Analyst
Category: Data Science
English level: upper
Years of experience: 0.5

I have spent the past 10+ years experiencing different business domains, and since last year I have been following my passion for data and my desired career strategy, developing myself as a data-driven professional, digging deeper into the knowledge of working with Big Data, and I am planning in nearest future to become a master in data analytics. 
I am proud of the realized projects and good responses of clients. I have successfully finished a Data Science Bootcamp, Tableau Analyst course, Python programming course, KPMG Data Analytics Virtual Internship. I am a self-learner and develop my knowledge of data analysis every day.
· Data preprocessing and making predictions project for an e-commerce company. I have made a full circle of data analysis including activities: understanding the data distributions, feature engineering, data transformations, modeling by using statistical analysis, and Python (Numpy, Pandas, Scikit-learn, Seaborn). In the end, I presented some data insights with Tableau and multiple regression model results with Python.  This work was successfully processed further by the client.
· Data quality assessment report for a retail business. I have explored data type, missing values, duplicates, out-of-range values, impossible data combinations, invalid data, and then replacing, modifying, or deleting these inaccurate records in the dataset using Python (Numpy, Pandas, Scikit-learn). During this project, I have practiced six dimensions of the data quality approach and applied it for the most effective data quality assessment in my report.
· Trouble clients’ analysis project. I have explored and analyzed a specific group of customers (using filtering and aggregating in Python), creating its visual analysis report via Tableau for monitoring the situation on regular basis, made a presentation of findings to the client using Tableau story.
· Data manipulation project. I have analyzed, filtered, and adjusted the data to client requirements using DAX via Power BI and engineered analytical report.
· Other projects where I analyzed data by using MySQL, Python libraries, Tableau Desktop.
Don't want to use mainly Excel for data analysis, I am fond of working with such tools as Python (Jupyter Notebook), SQL (MySQL, PostgreSQL), and Tableau Desktop.