Hi, I'm Maxim 👋 Aspiring Data Analyst with a strong interest in data analysis, visualization, and machine learning.
This repository contains my portfolio projects built with Python using real-world and simulated datasets.
- 📍 Based in Ukraine
- 📊 Focus: Data Analytics / Product Analytics / OSINT Analytics
- 🧠 Currently focusing on learning SQL
- 🎯 Goal: Become a Data Analyst / Product Analyst / OSINT Analytics
- Languages: Python
- Libraries: pandas, numpy, matplotlib, seaborn, scikit-learn
- Tools: Jupyter Notebook, Git, GitHub
- Concepts:
- Data Cleaning
- Exploratory Data Analysis (EDA)
- Data Visualization
- Machine Learning (Regression & Classification)
- Product & Marketing Analytics
Analysis of sales data to identify revenue patterns, top products, and seasonal trends.
Skills: EDA, feature engineering, time series analysis
Exploration of movie and TV show data to analyze trends in genres, countries, and content growth.
Skills: data cleaning, text processing, visualization
Analysis of salary distribution across countries, roles, and experience levels.
Skills: aggregation, comparative analysis, business insights
Built a regression model to predict apartment prices.
Skills: Linear Regression, model evaluation (MAE, MSE)
Predicted survival using classification models.
Skills: Logistic Regression, Random Forest, feature importance
End-to-end pipeline: EDA + machine learning for user purchase prediction.
Skills: full pipeline, feature encoding, modeling
Real-world dataset analysis with customer insights and Pareto principle.
Skills: customer analytics, revenue analysis, Pareto (80/20)
Evaluation of marketing performance using key metrics.
Metrics: CTR, CR, CPA, ROI
Analysis of user behavior, segmentation, and conversion.
Skills: product analytics, segmentation, behavioral analysis
- Data cleaning and preprocessing
- Exploratory data analysis (EDA)
- Data visualization
- Business metrics (CTR, CR, CPA, ROI)
- Machine learning (regression & classification)
- User behavior analysis
- Product thinking