Position: Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 4


Researched and developed ML applications for Natural Language Processing tasks in fintech.

- Implemented a news monitoring system using a multi-label linear classifier. This task implied working with taxonomies.
- Built a generic experimentation pipeline of unsupervised hierarchical multilevel multi-label classification for different text domains. As part of the project, I was working in collaboration with a knowledge engineering team on improving unsupervised keyword-driven classification techniques and implementing word sense disambiguation methods for improving keyword- based Unsupervised Text Classification. 
- Implemented a relevance filtering system. This task implied researching and exploration of pre- trained embeddings (GloVe, Spacy, Word2Vec, Universal Sentence Encoder, Transformer-based encoding) as well as embeddings to be trained (TF-IDF, RNN-based encoding).
Implemented a facts extraction system based on a question-answering transformer-based model. As part of a task, worked on the collection and annotation of domain-specific data.