Experience level:
1-3 years
Education level:
Bachelor
Languages:
Russian: Native
English: B2
Serbian: A1
I am a Data Analyst and Machine Learning Enthusiast with hands-on experience in real-world data projects. Skilled in Python, SQL, and popular ML frameworks such as Scikit-learn, LinearRegression, ForestRegression, CatBoost, and TensorFlow. Strong knowledge in database design and SQL querying (MySQL, MS Access) Over the last two years I have applied data science to solve practical problems in healthcare analytics, finance, and business intelligence. I built ML models to predict in-hospital mortality (sepsis), analyzed company expenses for budget forecasting, and developed custom dashboards and automated reports using Bitrix24 BI tool and data visualization libraries such as Seaborn, Matplotlib, and Plotly. I’m currently seeking for Junior/Middle positions or internships in Data Analytics, Data Science, or ML Engineering in Serbia where I can grow and contribute to impactful, data-driven decisions.
Stack: Bitrix24, SQL
Developed BI reports for management and departments, providing clear analytics and key performance indicators (KPIs) on sales and leads.
Streamlined data sets by eliminating duplicates and errors, improving data quality and processing speed by 25%.
Analyzed large datasets to identify business patterns, increasing process transparency and helping define strategic priorities.
Visualized all reports in Bitrix24, simplifying data access and enhancing information perception.
Developed predictive models for in-hospital mortality due to sepsis.
Utilized machine learning methods, including Decision Tree, TensorFlow, CatBoost, and Logistic Regression, to analyze medical data.
Performed data preprocessing: cleaning, normalization, and unification.
Achieved 85% prediction accuracy by optimizing model hyperparameters.
Stack: Python (Pandas, Scikit-learn, Matplotlib), Google Colab, Decision Tree, TensorFlow, CatBoost, Logistic Regression.
Stack: Python, Pandas, Seaborn, Pyplot, Sklearn.
Conducted analysis of cost reports, identifying key trends and patterns.
Compiled statistics and examined the impact of external factors on company expenses, enabling more accurate risk assessment and budget forecasting.
Developed clear and informative visualizations using Seaborn and Pyplot, significantly improving the team’s understanding of the results.
Stack: MS Access, MySQL
Designed a database structure to store information about transport and employees.
Utilized MySQL Workbench to organize data, reducing the time required to retrieve necessary information.
Analyzed data, including export volumes and order frequency trends.
Created reports and visualizations using Python (Pandas, Seaborn), enabling the management to make strategic decisions.
Developed a centralized data repository that streamlined the monitoring of key business metrics.
Programming Languages: Python, SQL. Data Analysis: Pandas, NumPy, Seaborn, Matplotlib, Pyplot. Machine Learning: Scikit-learn, CatBoost, TensorFlow, Logistic Regression, Decision Tree. Database Management: MySQL, MySQL Workbench, MS Access. Business Intelligence (BI): Data visualization and reporting in CRM Bitrix24. Data Preprocessing: Data cleaning, normalization, and feature engineering. Tools: Jupyter Notebook, Visual Studio Code, BI platforms. Project Management: Analytical thinking, risk assessment, and strategic planning. Other Skills: Report creation, data visualization, and process automation.