Position: Data Scientist / Machine learning / Deep learning engineer
Category: Data Science
English level: upper
Years of experience: 2

I used to work with projects from scratch with much domain research involved. So I can state the problem clearly, finding the optimal solutions and implement them quickly. Also, after working with unstructured and noisy data I know how to find relevant predictors and clean unnecessary ones. 

In the betting project, we increased the revenue by 20% compared to the traditional approach, starting the project from scratch with no domain knowledge to help.

In the micro-credit scoring project, I found relevant variables and constructed the machine learning model which predictions helped the main model to estimate loaners with no credit history.

Not all my findings happened to be successful, but I am always trying to get all from what I have.
I have experience in developing predictive and modeling systems with the use of machine learning. These are projects I have worked on:
1. Credit scoring for micro-credit loaners using mobile data. I was responsible for discovering significant predictors, providing analytical insights and constructing the machine learning model for improving main model scoring. This task involved dealing with noise and testing many hypotheses. We also used open-source data together with extensive scraping to complement our internal sources. In the end, we discovered significant features which boosted our traditional scoring.

2. The development of an automatic horse racing betting system. Made a multilayer model for predicting the winner in a horse race and following budget allocation system. Increased revenue by more than 20% compared to the traditional approach.

3. Computer vision project. My pet-project that I am actively working on now. It is about using GANs for removing the shadows from images. I have conducted extensive experimenting in the domain and gained much experience in computer vision with PyTorch.

I have much experience with machine learning modelling, working on analytical projects and dealing with unstructured, noisy data.
I am passionate about working on interesting projects, especially computer vision/deep learning-oriented.

Have strong skills with Python and DS packages(pandas, numpy, scipy), machine learning(scikit-learn, xgboost, lightgbm), deep learning frameworks(PyTorch, TensorFlow).