Position: junior data science
Category: Data Science
English level: upper
Years of experience: 0.5


Technology stack:
• Python framework: numpy, pandas, scipy, scikit-learn,;
• Exploratory Data Analysis (EDA): feature engineering, feature selection, preprocessing e.t.;
• Data visualization: plotly.express, seaborn, matplotlib;
• Supervised Machine Learning: LinearRegression, LogisticRegression, DesitionTreeClassifier,
RandomForest, XGBoost, CatBoost.
• Unsupervised machine learning: Kmeans, EM, DBSCAN.
• PostgreSQL.

Work Experience:
Projects in Data Science samples:1. Bank - attract customers to open a deposit. Data analysis, identification of patterns and
the search for decisive factors that influenced the fact that the client invested in this
bank.
2. Online store - segment existing customers, interpret these segments and determine the
strategy of interaction with them. Construction of a model of clustering of clients on the
basis of their purchasing power, frequency of orders and the term of the last purchase.
3. City taxi - Build a model that will predict the total duration of a taxi ride around the city.
4. Recommendation system for Ukraine clinics