Position: Machine Learning Engineer
Category: Data Science
English level: upper
Years of experience: 2

Created more than 6 pet projects in different fields of Machine Learning (NLP): Question Answering, Named Entity Recognition and Relation Extraction, Sentiment Analyses, Text Summarization, Topic Modelling, and Text Classification.

Hackathons Experience:

1) Hack4retail:1st place on the leaderboard
Task: Optimize dark store items placing
Solution: Optuna, Genetic Algorithms

2) PTI Hack 2022: 3rd place
Data Science Hackathon 
Task: Predict the probability of deal closing
Solution: building a Classifier, then using LightGBM and CatBoost separately, then stacking them to predict the probability
Commercaial Experience

Machine Learning (NLP) Engineer at Knowledgator Engineering (a Life Sciences data analytics software company).


Pet Projects

1) NLP Dialog System
One-Class Classification, Question Answering,  Natural Language Generation, Text Summarization, Sentence Similarity
Task: Build a bot to answer Data Science interview questions and perform NLG
Solution: OneClassSVM, AutoModelForSeq2SeqLM, Sentence Transformers, Cosine Similarity, BERT pre-trained on SQUAD Dataset, DialoGPT

2) Twitter Sentiment Classifier
Multiclass Classification
Task: Classify tweet sentiments
Solution: TF-IDF, LinearSVM, t-SNE

3) Chemical Named Entities Extractor
Named Entity Recognition
Task: Extract chemical-named entities in IOB annotations from the CHEMDNER corpus
Solution: CRF, BERT

4) CPU Recognition Pet Project
Data Engineering, Computer Vision (Oct 2021 - Feb 2022 )
Worked in a team of 4 people. Responsibilities: Parsing and labeling dataset for CPU recognition with YOLO
Seek for gaining new knowledge, extending experience, and implementing SoTA solutions to real-life tasks. Willing to join the professional team to work on ML Projects