Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 2


For 1.5 years have worked as a data scientist in an automotive project. Built a system for road coverage quality prediction from vehicles' inertial sensors data. Also worked on the algorithm to estimate friction between vehicles' tires and surface of the road, which required a comprehensive EDA. Used AWS, libraries for data analysis (numpy, pandas, sklearn), data visualisation (matplotlib, seaborn, plotly), supervised learning tree-based algorithms (XGBoost, Random Forest), unsupervised learning dimensionality reduction (PCA, TSNE) and clusterisation (KMeans, DBSCAN) algorithms.
 
Separately, conducted research and experiments in computer vision and natural language processing fields:
CV: embryos quality image classification, face generation (VAE and GAN), real-time weapon detection (YOLOv8)
NLP: browser bug-reports classification (RNNs), question answering (LLMs and BERT-like models), invoice question answering (LLMs).