Theoretical background: statistics, calculus and algebra. ML experience: Computer Vision, Imbalanced classification, Deep Learning, Anomaly detection, Survival analysis, Recommenders.

I apply different kind of data manipulations, statistics and machine learning techniques to extract knowledge from market data and generate ideas for algorithmic trading. Ideas are transformed into models which I prototype via Python, R and then - implementation on c++ new strategies for trading. Also, I create different tools and dashboards for data visualization, manipulation, analysis, analytical tools, parsers, scrapers, different "working horses", which works on daily basis with different data sources.
rience with "Big Data" and machine learning:

Scoring model building (assessing the client's creditworthiness, Gini=65%)
Development of mathematical models for computer vision task (automatic search of objects on an image)
Clients outflow/inflow modelling (clients outflow/inflow probability estimating, Gini=51%)
Recommendation systems development (the next customers purchases forecasting)
Insurance tariff systems development (CASCO, OSAGO)
Development of operational and management reporting, construction of models for the distribution of indirect costs