Sergii Lebid

Experienced finance professional with a strong background in banking and project management. Recently completed a Data Analytics Bootcamp at Ironhack Berlin, acquiring skills in Python programming, SQL, data visualization, and machine learning. Adept at data analysis, predictive modeling, and statistical analysis. Ready to leverage analytical and problem-solving skills in a data analyst role to drive business insights and improvements.

Data Analytics and Visualization:

Proficient in foundational data analysis and database management using Python (Pandas, NumPy) and SQL.

Experienced in creating data visualizations using Tableau to effectively communicate insights.

Knowledgeable in data cleaning, data modeling, and statistical analysis to support data-driven decision-making.

Financial and Economic Analysis:

Extensive experience in analyzing financial and economic performance, managing credit portfolios, and assessing risk.

Skilled in identifying trends and insights through data analysis to support strategic and operational decisions.

Capable of conducting fraud detection and prevention through detailed data examination.

Technical Skills:

Familiar with machine learning techniques for predictive modeling.

Competent in database maintenance, data exports, and data formatting.

Experienced with version control using Git and creating activity diagrams using Microsoft Visio.

Soft Skills:

Strong analytical problem-solving and critical thinking abilities.

Effective communication and report writing skills for presenting complex data.

Excellent teamwork and collaboration skills, with experience in training and developing staff.

Strong attention to detail and a commitment to delivering high-quality work.

Fraud Detection
Technologies: Python (Pandas, NumPy, Scikit-learn), SQL, Tableau
Conducted a comprehensive analysis of a company's credit portfolio to identify trends, anomalies, and potential fraud risks. Utilized data cleaning, analysis, and predictive modeling to derive actionable insights and support decision-making.

Wine Quality Prediction
Technologies: Python (pandas, numpy, matplotlib.pyplot, seaborn, train_test_split, cross_val_score, KNeighborsRegressor, GradientBoostingRegressor, MinMaxScaler, StandardScaler, GridSearchCV)
Developed machine learning models to predict wine quality based on chemical attributes, focusing on accurate regression models using Python's scikit-learn library.

Analyzing the Effectiveness of the New User Interface
Technologies: Python, Tableau
Conducted an experiment to compare the effectiveness of Vanguard's traditional online process (Control Group) with a new, modern User Interface (UI) and in-context prompts (Test Group) to evaluate if the changes lead to higher process completion rates and better user experience.

Analysis of the Job Market for Data Analysts in the USA
Technologies: Python
Researched to determine the position of data analysts in the income hierarchy across different states, providing insights into the job market for data analysts in the USA.

• Date of Birth: 03/09/1979
• Nationality: Ukrainian
• Marital Status: Married