Position: Data Scientist
Category: Data Science
English level: intermediate
Years of experience: 0

Kaggle Notebooks Contributor:
- Churn prediction (EDA, Random Forest and Metric methods)
- Vodafone Music prediction (Logistic Regression, SVM, XGBoost)
- Optimization Problems in ML: Gradient Descent Modifications (in progress)
Certificates on Coursera:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
- Convolutional Neural Networks
Certificates on Stepik:
- Introduction to Data Science and Machine Learning 
- Machine Learning algorithms
- Neural Networks and Computer Vision 
- Special Neural Network Architectures
— 1,5 year experience with Python.
— OOP, algorithms and data structures.
— Scikit-learn, Imbalanced-learn, Xgboost, Pandas, Numpy.
— SQL, Git, Docker.
— Knowledge of ML algorithms.
— Statistics, probability theory, linear algebra.
— Non-commercial experience in EDA, solving regression, classification and Computer Vision tasks on kaggle competitions, online cources and university course.
— Knowledge of DL basics and NN architectures. Non-commercial experience in Computer Vision tasks.
Looking for new experience, new people and new ideas to do)