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Евгеній
Аналітик
- Considering positions:
- Аналітик, аналітик з маркетингу, технічний спеціаліст, Web-аналітик, адміністратор баз даних
- Age:
- 35 years
- City of residence:
- Odesa
- Ready to work:
- Mykolaiv
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EVGENIY MIGDAL
Junior Data Analyst | Python | SQL | Machine Learning | BI
Ukraine | Email: [open contact info ](look above in the "contact info" section) | Phone: [open contact info ](look above in the "contact info" section)
GitHub: github.com/EvMiga | LinkedIn: [open contact info ](look above in the "contact info" section)
PROFESSIONAL SUMMARY
Data Analyst with over one year of hands-on experience working with real-world datasets, performing exploratory data analysis (EDA), building machine learning models, and generating actionable insights. Certified by IBM (Data Analyst Professional Certificate). Experienced in SQL querying, Python-based analytics, feature engineering, data visualization, and AI-assisted data processing. Focused on delivering data-driven solutions and business insights.
TECHNICAL SKILLS
• Programming: Python, SQL
• Data Analysis: Pandas, NumPy, SciPy, Statsmodels
• Machine Learning: Scikit-learn, LightGBM, TensorFlow (basic)
• Data Visualization: Matplotlib, Seaborn, Plotly
• Databases: MySQL, PostgreSQL (JOIN, CTE, Window Functions)
• Tools: Jupyter Notebook, Git, Excel, Power BI (basic)
• AI & Generative Tools: Hugging Face Transformers, DataRobot, CTGAN, Mostly AI, Microsoft Copilot
• Data Techniques: EDA, Data Cleaning, Feature Engineering, Correlation Analysis, Model Evaluation (ROC-AUC, Precision, Recall)
• API & Data Integration: REST API, Requests, JSON processing
PROJECT EXPERIENCE
Data Analyst (Independent & IBM Skill Network Projects) | 2024 – Present
• Analyzed open-source and real-world datasets (sales, customer behavior, socio-economic indicators)
• Performed data cleaning, preprocessing, and feature engineering
• Built classification and regression models using Scikit-learn
• Conducted correlation and statistical analysis to identify key drivers
• Created interactive visualizations and analytical reports
• Worked with APIs and integrated external data sources
• Applied Generative AI tools to enrich structured datasets
• Generated synthetic data for testing and model robustness validation
CERTIFICATIONS
IBM Data Analyst Professional Certificate
ADDITIONAL INFORMATION
English: Elementary(A2|B1)
Open to remote
Junior Data Analyst | Python | SQL | Machine Learning | BI
Ukraine | Email: [
GitHub: github.com/EvMiga | LinkedIn: [
PROFESSIONAL SUMMARY
Data Analyst with over one year of hands-on experience working with real-world datasets, performing exploratory data analysis (EDA), building machine learning models, and generating actionable insights. Certified by IBM (Data Analyst Professional Certificate). Experienced in SQL querying, Python-based analytics, feature engineering, data visualization, and AI-assisted data processing. Focused on delivering data-driven solutions and business insights.
TECHNICAL SKILLS
• Programming: Python, SQL
• Data Analysis: Pandas, NumPy, SciPy, Statsmodels
• Machine Learning: Scikit-learn, LightGBM, TensorFlow (basic)
• Data Visualization: Matplotlib, Seaborn, Plotly
• Databases: MySQL, PostgreSQL (JOIN, CTE, Window Functions)
• Tools: Jupyter Notebook, Git, Excel, Power BI (basic)
• AI & Generative Tools: Hugging Face Transformers, DataRobot, CTGAN, Mostly AI, Microsoft Copilot
• Data Techniques: EDA, Data Cleaning, Feature Engineering, Correlation Analysis, Model Evaluation (ROC-AUC, Precision, Recall)
• API & Data Integration: REST API, Requests, JSON processing
PROJECT EXPERIENCE
Data Analyst (Independent & IBM Skill Network Projects) | 2024 – Present
• Analyzed open-source and real-world datasets (sales, customer behavior, socio-economic indicators)
• Performed data cleaning, preprocessing, and feature engineering
• Built classification and regression models using Scikit-learn
• Conducted correlation and statistical analysis to identify key drivers
• Created interactive visualizations and analytical reports
• Worked with APIs and integrated external data sources
• Applied Generative AI tools to enrich structured datasets
• Generated synthetic data for testing and model robustness validation
CERTIFICATIONS
IBM Data Analyst Professional Certificate
ADDITIONAL INFORMATION
English: Elementary(A2|B1)
Open to remote
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