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

Kaggle competitions:
* Web-user identification task (LogisticRegression).
Result: 90th place among 5300 participants (top 2%);
* Restaurant Rating prediction (RandomForestRegressor). Result: 30th place among 772 participants (top 4%).
* Image Classification with Transfer Learning (Microsoft ML Bootcamp). 
Result: 11th place (top 4%) among 315 participants.
For the last two years I have been actively engaged in self-development in data science: from EDA to Neural Networks. Problem Solving Experience: Regression,
Classification, Clustering, Dimensionality Reduction, Object Recognition and Time Series Forecasting. Experience with the following methods: LinReg, SGD, LogReg, kNN, RF, XGBoost, KMeans, PCA, LAMA, CNN, RNN.
I also have two higher education: technical and economic, and 12 years of successful career in FMCG production management.
I enjoy solving classic data science problems such as regression, classification and clustering. In addition, I have chosen computer vision as my main specialization.