Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 0.5

- participation in Neurohackathon (hors concours).
- feature engineering and Big Data preprocessing for the healthcare project
Data Analyst in a Data Science team responsible for exploratory, statistical data analysis, and visualization, feature engineering, preparing data for the models and engaged in models development. 

Experience: 9 months

Stack: Python, Pandas, Scikit-learn, NumPy, StatsModels, Matplotlib, Keras, Seaborn, Plotly, Dash, Tableau, PySpark, Bitbucket, Jira, Selenium.

Key responsibilities: 
• exploratory data analysis
• data preprocessing
• feature engineering
• statistical analysis 
• visualization

Additional responsibilities:
• machine learning models development

Projects:
1. Computer Vision domain. Developing a realtime webcam face recognition tool based on OpenCV libs. The tool defines unique faces, their age and gender, tracks emotions and builds an analytical dashboard.
2. Urban domain. Developing a visualization module based on Dash and Plotly. The module aims to provide daily human mobility analysis of different city zones using telecom data and show the most popular routes.
3. Agriculture domain. Building the yield forecasting model based on historical yield data, historical weather data, and protocols about crop favorable growing conditions. 
4. Healthcare domain. Exploring medical protocols and creating association rules based on symptoms, comorbid conditions and laboratory analysis for revealing diseases unnoticed by doctors.
5. Automotive domain. Developing a part of the recommendation system based on statistical analysis.
Strongly interested in diving deep into Data Science and designing complicated machine learning solutions.