Hello, I am Data Scientist with over a year of experience in data analysis and BI reporting development. In the past, I have built predictive models (achieving 85% accuracy), automated BI reports, and visualized data usi…
Hello, I am Data Scientist with over a year of experience in data analysis and BI reporting development. In the past, I have built predictive models (achieving 85% accuracy), automated BI reports, and visualized data using Python. My resume is attached.
English level: B2, currently learning Serbian independently. Open to remote work.
Telegram: @mysweetestmelody
Built predictive models for in-hospital mortality due to sepsis using machine learning algorithms.
Optimized model accuracy to 85% through hyperparameter tuning and rigorous data preprocessing.
Enhanced risk assessment and patient care strategies.
Performed model interpretation using SHAP and permutation importance to ensure transparency.
Visualized clinical insights using Matplotlib and Seaborn to improve communication with medical staff.
Documented the entire ETL pipeline and created a scheduled workflow using Airflow for model retraining and reporting.
Improved trust in AI-driven decisions.
Built predictive models for in-hospital mortality due to sepsis, optimized model accuracy to 85%, performed model interpretation, visualized clinical insights, documented ETL pipeline
Developed BI dashboards in PowerBI to provide actionable insights for HR department.
Built data pipelines for extracting and aggregating sales and marketing data across departments.
Implemented real-time monitoring for key metrics, enabling faster decision-making.
Improved KPI tracking efficiency by 20%.
Conducted A/B testing to compare the efficiency of traditional and updated hiring processes.
Analyzed HR metrics, revealing that the new process reduced time-to-hire by 15%.
Increased recruitment efficiency.
Developed BI dashboards in PowerBI, built data pipelines, implemented real-time monitoring, conducted A/B testing, analyzed HR metrics
Conducted detailed analysis of company expenses, identifying key trends and external impact factors.
Developed a recommendation system to optimize costs, reducing operational expenses by 10%.
Analyzed company expenses and built cost prediction models (Random Forest, PyTorch), reducing operational costs by 10%.
Automated reporting workflows, saving 15+ hours per month.
Improved budget forecasting and financial decision-making.
Conducted detailed analysis of company expenses, developed a recommendation system, built cost prediction models, automated reporting workflows
Designed and maintained a centralized database in MySQL and ClickHouse, improving query speed by 30%.
Worked with large and unstructured datasets, including product logs and customer behavior data.
Reduced data retrieval time by 30% and streamlined business operations.
Enhanced operational efficiency.
Designed and maintained a centralized database, worked with large datasets, reduced data retrieval time
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