I have basic knowledge in mathematics and programming:
- probability theory, statistics, mathematical modeling, game theory, optimization methods, graph theory, one- and multivariate analysis of variance;
- recommendation systems, databases, object-oriented programming, algorithms and data structures, graphs of knowledge;
- data modeling and analysis
I want to develop in the field of Data Science, machine learning, Python development
Knowledge of foreign languages:
English (Upper - Intermediate);
German (B1);
French (with a dictionary);
Russian (available)
I have experience writing programs in languages:
C
C++
HTML; CSS
SQL
Python
Neo4j
I work in Microsoft Office including Excel and Project
2016-2019
2017-2019
- correlation analysis of geolocation dependency and time frame of commissioned offense in Sacramento for 2006.
I obtained qualification: Bachelor's degree in Applied Mathematics
Performed and defended scientific and practical work on the topic "Stationary point vortex systems in perfect fluid";
As part of the WEB Development course, I have created a multi-page site for learning German - online, using text and media files for training, as well as links to YouTube videos;
In Neo4j, I designed a data model for the task of "Organization of staff work in medical institutions", whose main purpose was to build an optimal strategy and calculate the time of healthcare workers for each patient based on the analysis of patient factors, staff and the specifics of the department in the hospital.
As part of the Data Analysis course, I conducted a correlation analysis of geolocation and timeframes for the probability of committing crimes in Sacramento in 2006. The optimization model was tested and verified on the basis of the data used in the 2006 time interval.
Performed scientific work outside the scope of the special course "Data Analysis":
- data collection, factor analysis and analytical and synthetic data processing for the American firm "Apollo". The optimization model was adopted, tested and verified on the basis of the data used in the time interval from 2003 to 2014.;