Soft-, ML-, Simulation Engineer and Data Scientist
I strongly believe that there is no perfect tool for each job, but more or less usable technologies and approaches - be open minded to find the suitable one.
If I am given the freedom to implement a project with no previous technical limitation, I promise, I'll make sure that the best possible stack is used. The codebase is clear, simple and maintainable. Documentation is present AND USEFUL!
I constantly learn new things both on my work and outside of the office hours. I like combining new approaches and theories together for existing problems. Giving back to the community through a talk or a workshop is also a part of my life
AMLD2019: Data analysis workshop organizer
Working student, Graphics manipulation, design
Working student, front end developer (Angular.js, Bootstrap, JS)
Fulltime software developer (Data Engineering, Backend Development, NLP)
Machine Learning Engineer (Data preparation; streaming; chron jobs; backend engineering; highly specific, high performance simulation framework)
The bachelor thesis consisted in proving that classical portfolio models are ineffective on modern Russian stock exchanges. Thus I suggested an adopted approach for choosing the portfolio for a private investor.
The goal of my second bachelor thesis was to check what language is more suitable for an econometric task written on the beginner level. Python and R were chosen for comparison, since these two languages are heavily used by both scientific and non-scientific communities. To answer this question I have written two identical Programs (with respect to the language's features and idiomatic style) in Python and R and have run performace and memory usage tests. I have also compared subjective usability (ease of use, documentation quality, community) of the langages.