Sem Leontev
I am an experienced Data Analyst with over 8 years of expertise in data analysis, statistical modeling, and machine learning. My proficiency lies in utilizing Python, R, SQL, and data visualization tools such as Tableau. I hold a Master's degree in Business Analytics, which has provided me with a strong foundation in the field.
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Data Science Projects
Forecast US multifamily market growth using random forest, time-series and dynamic regression [R , Python]
The project is focused on forecasting multifamily market growth for 390 metro areas over the next 5 years. Using Python and R as programming languages, I employed techniques such as Random Forest, Time-series forecasting, and Dynamic Regression. The objective was to provide accurate predictions and insights into future market trends. Through extensive analysis and modeling, I created a robust forecasting framework that provides valuable information for strategic planning and investment opportunities in the multifamily real estate sector. This project serves as a valuable tool for making informed decisions in the industry.
Interactive dashboard for multifamily housing market forecast. 2023 - 2027 years [Tableau]
For this project, I utilized my forecasting data to create an interactive Tableau dashboard. The dashboard provides users with the ability to visualize and explore the exact forecasted growth rate for each of the 390 metro areas over the next 5 years. By integrating the forecasting outcomes into a user-friendly interface, stakeholders can easily access and analyze the projected growth rates specific to their desired metro areas. This interactive tool enhances decision-making capabilities and facilitates a deeper understanding of the multifamily market landscape on a granular level.
Predict Super Bowl 2023 results using Random Forest [Python]
The NFL Super Bowl is only a few days away and I am actually feeling excited about it this year. As a curios person I cannot wait for a few more days to see the winner so I thought it’d be interesting to try to predict the winner beforehand. I used Python and RandomForest Classifier to predict the winner, and then use Regressor to make a guess on the score. Here is my way to predict the Super Bowl outcome.
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