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Aleksandr

  • Data Scientist, Machine Learning, Backend developer
  • Krasnodar, Russia
  • May 27, 2019
Telecommute Information Technology

Personal Summary

Strong knowledge of Python, PySpark;
basic knowledge of C ++, JS;
As well as HTML, CSS, SQL.

I have ex perience with:
- machine learning methods for solving the problem of classification, clustering, regression (including recommender
systems);
- statistical data analysis;
- data types: numeric, tex t (nltk), images (opencv);
- Python libraries numpy, pandas, sklearn, keras, tensorflow, tpot;
- tools for working with big data pyspark;
- parsing sites (request, selenium, pyppeteer, beautiful soup);
- mongodb, elasticsearch
- writing of high-load services (flask, flask restplus, django, tornado, celery, rabbitmq)
- create UI for demo (react)

Skills:
- I can work both independently and in a team;
- I choose solution methods based on the specifics of the task, data types, I find alternative solutions;
- I quickly learn new tools, do not limit myself to studying
- creation and optimization of algorithms


Professional Skills
Python Ex pert
JavaScript Advanced
Machine Learning Advanced
MongoDb Ex pert
ElasticSearch Ex pert
PySpark Advanced
Flask Ex pert

Work Experience

Data Scientist, Machine Learning, Backend developer
Apr 2017 - DecisionMApper

Data Scientist, Machine Learning, Backend developer
Duties:
- collection and preprocessing of data: creating parsers, preprocessing tex t data and images, normalizing data,
filtering outliers;
- data analysis, identification of patterns, search for solutions;
- building learning models;
- assessment of the quality of the models;
- optimization;
- visualization of results.
-creation API;
-creation UI for demo;

W orked on projects:
- cell detector. Development of a service for the detection and classification of blood cells using convolutional neural
networks.
- Analysis of the real estate market - identifying areas of the city with the most profitable offers with low average
annual payback of real estate and creating a service for collecting data and identifying areas with similar offers that
are more profitable;
- Creating a service for processing and analyzing large and regular data;
- Auto-ml. Development of a service for automating data processing and machine modeling
learning.
- chatbot_builder. Creating an API for building chat bots and test UI.
- Isolation and recognition of tex t from invoice images.
- Natural language processing - tex t classification, the creation of chatbots.
- Statistical data analysis, search for outliers, deviations, plotting linear regression;
- Hierarchical data clustering, clustering using the k-means method;

Education

Master's Degree
- Jun 2019 Taurida Academy of the Vernadsky Crimean Federal University