Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 1.5


Sentiment analysis and clusterization of user comments. Creation of a recommendation system which aim is to recommend some visually compatible items for a given one and measuring the quality of the initial system’s predictions. Creation of an application for goods customization specifically shoes with customer text input. Creation of an application for a text to image search using CLIP.

Technologies used:
Python
Pytorch
TensorFlow
Google Colab
Amazon S3, EC2
LSTM
CNNs
CLIP
VQGAN
Dall-E mini
Diffusion models

Responsibilities:
Collection, cleaning, processing and analysis of new and existing data sources
Model architecture selection and model training
Work results presentation


Training project on .Net platform

Technologies used:
C# programming language,
ASP.NET Core,
LINQ to SQL,
MS SQL Server,
HTML,
CSS,
JavaScript.

Responsibilities:
Developing functionality,
Participating in code review.


Master thesis: Action recognition in sports videos

Technologies used:
Python programming language,
Tensorflow,
Numpy,
Recurrent neural networks,
Convolutional neural networks

Responsibilities:
Data processing (Data augmentation, Dealing with class imbalance)
Build and train models for action recognition in sports videos,
Assess quality of models


Graduate work: Time series forecasting with neural network and statistical methods

Technologies used:
Python programming language,
Tensorflow,
Pandas,
Numpy,
Matplotlib,
scikit-learn,

Responsibilities:
Building a model,
Data processing,
Model's quality estimation