About Me
My name is Andrey,
and I am a Data Scientist with a passion for transforming data into actionable insights. I have a strong background in machine learning, statistical analysis, and data visualization.
With a keen eye for detail and a commitment to continuous learning, I thrive on solving complex problems and delivering data-driven solutions. I am proficient in Python, SQL, and data visualization tools like Power BI or Streamlit.
My goal is to leverage data to drive business decisions and create value. I am always eager to take on new challenges and expand my skill set.
In my free time, I enjoy exploring new technologies, running, and drawing.
Key Skills:
- Machine Learning (e.g., Regression, Classification, Clustering)
- Statistical Modeling and Hypothesis Testing
- Data Visualization (e.g., with Python libraries, Power BI)
- Data Preparation and Cleaning
- Python, SQL
Selected Projects
Funny thing, this website is also a little project :)
AI-Forecast
In this project, I developed an AI-powered forecasting tool using Snowflake, Python (neural network), and Power BI to automate business performance predictions, replacing a manual forecasting process.
View Details (click & scroll down)Streamlit Analysis & Data Scraping
Another concise summary of an interesting project. In this porject I wanted to see what ist possible with public data and some basics in Streamlit.
View Details (click & scroll down)Data Mart for Cost Centers
Development of a Snowflake Data Mart for Enhanced Data Analysis in Power BI
View Details (click & scroll down)Details: AI-Forecast
Detailed Description: This project developed an AI-powered forecasting tool using Snowflake, Python, and Power BI to automate business performance predictions, enabling faster, data-driven decision-making.
Technologies and Methods Used: Python, Pandas, Scikit-learn, SQL, Snowflake, TensorFlow, TensorBoard, (KERAS)
Challenges and Solutions: The challange was to tranform the data in the right strucutre and make sure the data is correct
Results and Impact: The new MAPE-Value was around 9%. Comparing to the old (20%) it was an improvement.
Back to Project OverviewDetails: Streamlit Analysis & Data Scraping
Detailed Description: This porject dealt with public data of a restaurant. I did some basic analysis. The main goal was to learn how easy it is to utilize streamlit for data visualization.
Technologies and Methods Used: Streamlit, BeautifulSoup, Python
Challenges and Solutions: Learning some interesting stuff is always a challenge and a solution.
Results and Impact: Insightful Dashboard
Back to Project OverviewDetails: Project Title 3
Detailed Description: A Data Mart, a focused subset of a Data Warehouse, improves data access for analysis. Built in Snowflake using SQL, this project delivered a Data Mart integrated with Power BI, enabling the client to conduct quick, user-friendly data analyses.
Technologies and Methods Used: SQL, Snowflake, DBT, ETL.
Challenges and Solutions: The expanding Data Warehouse hindered data access and usability for non-technical users, addressed by building a Snowflake Data Mart with SQL for targeted retrieval and Power BI for intuitive visualizations.
Results and Impact: The Data Mart streamlined data analysis, enabling quick and accurate insights. Power BI's user-friendly interface improved user engagement and enhanced decision-making efficiency across the organization.
Back to Project Overview