Position: Data Analyst
Category: Data Analyst
English level: upper
Years of experience: 3

-Created reports and models were regularly utilized by bank sales teams to boost sales and make branch performance decisions.
-Increased customer service speed, which resulted in less crowds at branches, despite the fact that the number of clients remained constant in comparison to prior times.
In my previous work experience, I have used a variety of algorithms and techniques to analyze data and make performance forecasts. Specifically, I have used AdaBoost, Linear Regression, and Random Forest Classification algorithms in Python to produce performance forecasts for regional branches based on internal bank and macroeconomic indicators.
I have also created models to determine which branches should be open on weekends and holidays, optimal number of branch employees (teller, cashier), as well as one to assess their productivity and profitability using historical sales data, market trends, and customer analysis. Additionally, I have experience creating dashboards utilizing Tableau for visualization and Python for automation for credit and non-credit sales as well as mortgage sales.
Furthermore, I have expertise in creating a branch rating system based on loan and non-lending product sales, and using the K-Nearest Neighbors (KNN) technique in R to create branch clustering for intra-bank competition. I have also used the Prophet Model in Python to create quarterly sales forecast reports for loan products and the Random Forest Classification model in Python to generate customer feedback.
Finally, I have experience analyzing marketing and sales initiatives to determine the most effective campaigns, using Power BI for visualization.
I am eager to cooperate with driven and collaborative teams. The major aim is to use my knowledge and experience to assist the company in becoming more effective and efficient, while also acquiring new skills from my coworkers. In our line of business, I always expect to see a corporation that cares about its people in order for them to be highly motivated.