Stockholm-based data scientist and digital marketing expert with a background in E-Commerce and Management. With an entrepreneurial mindset, I focus on innovative data-driven solutions that drive growth.
| Project | Skills & Tools |
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Used E-Bikes Price Prediction App (private)
- Data Mining: over 15.000 scraped ads from Blocket.se - Data Mining: over 1800 scraped e-bike models from PriceRunner.se - Data Mining: over 2000 scraped e-bike listings from Rebike.com - Conducted comprehensive analysis of the Swedish electric bike market and international players, providing insights for strategic decision-making. - Developed predictive machine learning models with outstanding results (97-99% accuracy). - ML: created a separate app for yearly rental price prediction - Created insightful reports, leveraging data analysis and machine learning model outcomes. |
CatboostRegressor, VS Code, Streamlit, Pandas, Seaborn, GridSearchCV,StandardScaler, Cross_val_score, Shuffle |
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UAE Real Estate Investments: Price Prediction App (public version) - Data Mining: 130.000 properties in Dubai - ML: created a machine learning algorithm for property valuation. R2 score is: 0.94 - ML: created a separate app for yearly rental price prediction - Created a web app that predicts property value based on property's features |
RandomForestRegressor, VS Code, Streamlit, Pandas, Matplotlib,Seaborn,LinearRegression, GridSearchCV, StandardScaler, Cross_val_score, Shuffle |
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Hackathon | Talent Squad | Data Science Participated in Data Science hackathon by Barcelona Digital Talent. Project "Influences on Academic Achievement". |
Results: 🥈 Individual Ranking #2nd Place. |
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Participated in Data Science hackathon by Barcelona Digital Talent. Project "Air Quality Classification". |
Results: 🥇 Individual Ranking #1 Place. |
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This Data Science project's goal is to conduct experiments with various metrics on e-commerce data. |
Metrics:
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Created a simple web app with cryptocurrency exchange rates over time. |
VS Code, the CoinCap API, Streamlit. |
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U.S. Inflation rate vs Fed Rate. 1983 - 2022 Analysis & Correlation between inflation (CPI) and the Fed Rate during 1983 - 2022; US national recessions (1990s, 2000s, Great Recession, Covid-19 recession) + pre & post recession periods. |
Exploratory data analysis, linear regression, data visualization, data preprocessing, data processing, correlation, pandas, numpy, seaborn, matplotlib, datareader, sklearn, pyplot, lineplot. |
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U.S. Home Prices vs. CPI in 2022 Overview of 2022: HPI vs CPI in the US (Forecasting and Analysis). 75 & 35 years of data analysed in order to forecast remaining 2022's months data on HPI & CPI. Forecasting is made using Prophet model. |
Data forecasting, exploratory data analysis, linear regression, data visualization, data preprocessing, data processing, prediction, pandas, numpy, seaborn, matplotlib, datareader, sklearn, pyplot, statsmodels, pystan, tsarplot, fbprophet, prophet. |
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Exploratory Data Analysis(EDA) on Residential Properties Data science project's goal is to determine the market value of real estate objects and to define typical parameters of residential properties. The real estate listing platform will use Exploratory Data Analysis' conclusions in an automated system to prevent fraudulent activities on the platform. |
Exploratory data analysis, data visualization, data preprocessing, data processing, histogram, boxplot, scatter matrix, categorization, scatter plot, fraud monitoring, numpy, seaborn, pyplot, python, pandas, matplotlib |
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[RU] Customer churn forecast for telecom operator Project's goal is to predict whether the client will leave the telecom operator in the near future or not. If it turns out that the user plans to leave, he will be offered promo codes and special plans. |
Machine learning, data analysis, regression, custom metrics, gradient boosting, logisticregression, randomforestclassifier, catboostclassifier, python numpy, scikit-learn, matplotlib. |