Data Analyst
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I served in the criminal police and worked with distressed assets in banks, and my passion has always been understanding the nature of things and the dependencies of phenomena on each other. If you like the series "Breaking Bad", have watched Harry Potter or The Lord of the Rings more than twice, and consider "The Last of Us 2" one of the best games of the decade, we're on the same wavelength.
You can view my CV or learn more about my professional path on LinkedIn by clicking on the icon above.
Portfolio
Data analysis
This section presents examples of data analysis projects I have completed. The projects are focused on exploratory data analysis, statistical analysis and A/B testing, as well as business performance analysis.
Identification of insights to use in making a decision on choosing an investment strategy.
Stack: Python (Jupyter Notebook)
Building and analyzing a sales funnel, studying the results of an A/A/B experiment.
Stack: Python (Jupyter Notebook)
Identification of patterns that determine the success of the game for planning an advertising campaign.
Stack: Python (Jupyter Notebook)
Analysis of the economic efficiency of user acquisition channels for the app.
Stack: Python (Jupyter Notebook)
Prioritization and analysis of hypotheses for increasing revenue in an online store. Conducting A/B testing.
Stack: Python (Jupyter Notebook)
Identifying dependencies and factors influencing pricing in the real estate market.
Stack: Python (Jupyter Notebook)
Machine Learning
This section presents examples of machine learning projects I have completed. The projects involve classification methods, regression, and neural networks. Additionally, all projects include data preprocessing and feature engineering.
Creating a model that predicts the user's musical preferences based on the history of listening to songs.
Stack: Python (Jupyter Notebook)
Creating a model for predicting avocado prices based on historical data.
Stack: Python (Jupyter Notebook)
Building a machine learning model for heart disease classification to predict the likelihood of its occurrence.
Stack: Python (Jupyter Notebook)
Development of a machine learning model for the classification of pulsar stars.
Stack: Python (Jupyter Notebook)