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Даниїл

Інтегратор AI-рішень та підтримки клієнтів (з навчанням)

City of residence:
Kryvyi Rih
Ready to work:
Remote

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DANYIL SOKURENKO
DATA SCIENCE ENGINEER

[open contact info](look above in the "contact info" section) PROFILE
[open contact info](look above in the "contact info" section)
Aspiring Data Scientist with strong foundations in Python, statistics, and
machine learning. Skilled in analyzing complex datasets and extracting
[open contact info](look above in the "contact info" section)
meaningful insights. Eager to apply analytical thinking to solve real-world
problems.
linkedin

EDUCATION PROJECTS AND EXPERIENCE
CUSTOMER CHURN PREDICTION
2022-2026
AKADEMIA FINANSÓW I BIZNESU VISTULA Developed a machine learning model to predict
Bachelor of Engineering in customer churn using Python and Scikit-learn
Computer Science Performed data cleaning, feature engineering, and
exploratory data analysis (EDA)
HARD SKILLS SOFT SKILLS Trained and evaluated multiple models (Logistic
Regression, Random Forest)
Programming: Python, SQL Data Storytelling
Python Libraries: Pandas, Attention to detail
HOUSE PRICE PREDICTION
NumPy, Scikit-learn, PyTorch Communication Teamwork &
Built a regression model to predict house prices using
Data Visualization: Plotly, Collaboration
advanced feature engineering techniques
Seaborn, Matplotlib Critical thinking
Handled missing data and encoded categorical
Machine Learning: Regression, Analytical skills
variables
Classification, Clustering, Risk Assessment
Applied models including Linear Regression and
Model Evaluation, Process Improvement
Gradient Boosting
Tools & Technologies: Git, Stakeholder Management
Jupyter Notebook, Docker Time Management &
Reduced prediction error (RMSE) through
(basic) Organization
hyperparameter tuning
Statistics: Hypothesis Testing, Adaptability
SALES FORECASTING (TIME SERIES)
Probability, Active Listening
Data Handling: Working with
Built a time series forecasting model to predict future
structured and unstructured
sales
data, ETL basics
Analyzed trends and seasonality patterns in historical
API Interaction
data
LANGUAGES Applied ARIMA and machine learning approaches
Improved forecasting accuracy compared to baseline
models
Polish - B2
English - B1
Ukrainian - native

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