Position: Data Scientist NLP / Machine Learning Developer
Category: Data Science
English level: upper
Years of experience: 2

Yandex and MIPT specialization "Machine learning and data analysis"
Professional certification prep course "Google TensorFlow Developer"
Neural Networks for NLP by Samsung Research
I have hands-on working experience with Python .
Skills:
+ Data collection and extraction (external APIs; scraping, parsing)
+ Data processing, aggregations (MongoDB (MQL), PostreSQL (SQL))
+ Working with classical data science toolkit : scikit-learn, xgboost, keras.
+ I specialize in natural language processing (NLP):  language models, vectorization, topic modeling. Familiarity with following tools: gensim, natasha, spacy, keras (tensorflow) for NLP tasks, as well as pytorch, transformers.
+ I feel comfortable integrating things together, working outside of jupyter notebooks. 
+ API development and micro-service architecture.

Projects:
+ Application for sentiment analysis of product reviews for English and Russian: several implementation from classical baselines, continuing with Keras neural networks and filnally with transfer learning, API endpoint by flask, webUI; data collection and labeling by hand;
+ Text generation work, based on LSTM-nets;
+ Text summarization work and application;
+ Punctuation restoration project: LSTM written in PyTorch;
+ Keyword generation work: applied topic modeling by gensim and syntactic parsing by spaCy;
+ Work on classifying company operation codes based on transaction graph;
+ Project for an American company for email automation: intent classification, entity extraction, FastAPI endpoint and demo interface;
+ Non-ML projects can be found on my github page.

I have job experience as developer in analytical company, currently I'm working with industrial NLP, with emphasis on text classification and entity extraction.
I am comfortable with the following tools: git, docker, docker-compose, other tools of good software engineer; confident Linux user.
I'm looking for "ML developer", "Data Science developer" or "Data Scientist" position with more emphasis on machine learning and lesser on back-end development, yet I'd prefer to create complete applications (services) participating on both sides, other than just doing analysis in notebooks. Relation of the project to NLP is a must.

Remote work only.