Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 4

- Winner of Data Science Haсkathon INT20H 
- Master of Science degree in Data Science and Mathematical Modelling. NTUU “Kyiv Polytechnic Institute”, Faculty of Applied Mathematics (graduate 2021)
- Exchange study in Sweden
- Started two DS projects from scratch
Passionate Data Scientist with a strong mathematical background.
Master's degree in Applied Mathematics.
Experienced in working with research projects, data collecting, engineering and preparing, classification/regression/clustering problems, feature engineering, time-series, imbalanced data, multi-label cases, metrics selection, interpretation of ML models etc, as well as defining DS project specifications and building DS architerture.
All important soft skills are surely present :)
More detailed experience is below.


Non-commercial projects:

- Dengue epidemic modelling (Research, Data Visualization, Time-series forecasting)
- Nocturnal Hypoglycemia prediction (Research, Data Analysis, Mathematical modelling)
- Sleep detection with wrist-worn accelerometer (Data Analysis, Deep Learning)
- Taxi demand forecasting (Data Visualization, Time-series forecasting)
- Fake news detection using Big Data tools (AWS, Apache Hive DB, PyHive, RDS MySQL, Data Analytics)
- Heart disease discovery (Data Analysis, Feature Analysis, ML multi-class classification approaches)
- The system of occupational morbidity risk assessments in medical staff (Research, Data Analysis, ML multi-label classification approaches, Interpretable ML, Imbalanced learning, Clustering algorithms, Feature Importance)


Commercial:

- Healthcare research project (from scratch):  
research of medical data & medical papers reviewing, building ML project architecture, defining data requirements, launching data collection, medical data engineering & preparing, testing baseline models.

- RecSys project (from scratch): 
research in music information retrieval, building ML project architecture, decomposing tasks, launching and supporting data collecting and data annotating processes (iterative to meet desired model accuracy), defining data requirements, combining different data sources, performing exploratory analysis, developing custom module for audio feature extraction, comparing regression and classification models for different tasks, tuning hyperparameters, defining metrics to correlate with business requirements, automatizing deployment & models re-training processes.

- Information analytical system (cybersecurity domain):
developing system modules (C#, Python), designing subsystem architecture, work with technical specifications, data engineering, training prediction models, performing descriptive data analysis, building reports and visualizations.
I am passionate about working with data and making data work for the purpose, so I seek interesting projects and companies where both of us can benefit from the cooperation.