Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 2.5

Education:
	Master’s degree in Applied and Theoretical Statistics (2018-2020)
	Bachelor’s degree in Statistics (2014-2018)
Taras Shevchenko National University of Kyiv. Faculty of Mechanics and Mathematics

Projects:

	“Hand-held groceries recognition using Residual Networks”, master's degree thesis 
Trained a residual neural net to classify groceries in customers’ hands.
	 “Handwritten Digit Recognition using Support Vector Machines and Logistic Regression”, bachelor's degree thesis. 
Created models (SVM, Logistic Regression) that classify images with handwritten digits. 
	“Prediction of coronary heart disease in the Western Collaborative Group Study” 
Created a model (Logistic Regression) that predicts the presence of the disease. 

Tech stack: Python (NumPy, Pandas, Matplotlib, Scikit-learn, Fastai, OpenCV)
Data engineer 
-	Collecting and processing (cleaning, transforming, structuring) data for computer vision tasks
-	Implementing image background segmentation with clustering algorithms/background subtraction
-	Developing data selection techniques to create clean, diverse and large-scale datasets
-	Automating scenarios generation for testing AI’s real life performance, creating descriptive classification reports
-	Creating scripts for data labelling automation
-	Creating and managing in-store products databases
Tech stack: Python (NumPy, SciPy, Pandas, Matplotlib, Scikit-learn, OpenCV), Excel