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Senior
Registration: 26.11.2021

Evgeny Brovkin

Specialization: Data Science
Data scientist with vast experience in deep learning, computer vision, machine learning, natural language processing and statistics. I've built models and brought insights for banks, multinational retail chains, and global restaurant services. I like challenging projects and bringing cutting edge technologies to work.
Computer Vision Data Scientists Python Numpy scikit-learn Python Machine Learning Machine Learning Engineer NLP pandas PyTorch AWS Azure Tensorflow
Data scientist with vast experience in deep learning, computer vision, machine learning, natural language processing and statistics. I've built models and brought insights for banks, multinational retail chains, and global restaurant services. I like challenging projects and bringing cutting edge technologies to work.
Computer Vision Data Scientists Python Numpy scikit-learn Python Machine Learning Machine Learning Engineer NLP pandas PyTorch AWS Azure Tensorflow

Portfolio

Retail customer detection and tracking system based on CCTV

Proof of concept of a detection and tracking system done for a worldwide beauty retailer. The system is based on deep neural networks and consists of a customer/staff recognition system, tracking, and action classification subsystems. The resulted system is used for advanced analytics using CCTV in stores. Participation: • Implemented and fine-tuned online tracker for multiple-object tracking problem • Implemented scoring and evaluation pipelines for the system • Augmented pre-trained models for people re-identification process of tracking

COVID-19 epidemiological model and sales impact analysis

A successful take on coronavirus spread modeling and sales impact analysis for a global sports retailer. We had brought theoretical results from the paper to a working state in a very short period of time. The resulting work impacted the decisions of top managers during the initial coronavirus outbreak. Participation: • Created and implemented the COVID-19 response model based on SIR epidemiological model via regression analysis and a system of differential equations. • Implemented country-wise sales impact models and data pipelines for retail and digital stores during the initial lockdown period in Europe

Customer segmentation for beauty retailer

A data discovery project for a beauty retailer. The project was a collaboration work of data science and user experience teams. We have applied machine learning algorithms to big data. The results were a documented data science environment on Microsoft Azure full of data reports with valuable insights. Participation: • Created data loading and preparation pipelines for further analysis using PySpark. • Made a number of analytical lab reports based on transaction data. • Clustered customers using machine learning algorithms into segments using PySpark ML module. • Analyzed correlations between geographical data and customer behavior.

Digital fashion mobile AR app

Mobile app powered by AR and deep learning / digital fitting room. A user can try new clothes or styles using only a smartphone. Participation: • Researched papers on related tasks solved via neural networks • Implemented model and pipeline for human pose estimation task • Realised cross-platform postprocessing library in C++, implemented Python binding for the library

Skills

Python
Computer Vision
Machine Learning
Natural Language Processing
Data Engineering
Communication
Project Management
Time Management

Work experience

Data Scientist
COVID-19 epidemiological model and sales impact analysis
.
A successful take on coronavirus spread modeling and sales impact analysis for a global sports retailer. We had brought theoretical results from the paper to a working state in a very short period of time. The resulting work impacted the decisions of top managers during the initial coronavirus outbreak. Participation: • Created and implemented the COVID-19 response model based on SIR epidemiological model via regression analysis and a system of differential equations. • Implemented country-wise sales impact models and data pipelines for retail and digital stores during the initial lockdown period in Europe
Data Scientist
Retail customer detection and tracking system based on CCTV
.
Proof of concept of a detection and tracking system done for a worldwide beauty retailer. The system is based on deep neural networks and consists of a customer/staff recognition system, tracking, and action classification subsystems. The resulted system is used for advanced analytics using CCTV in stores. Participation: • Implemented and fine-tuned online tracker for multiple-object tracking problem • Implemented scoring and evaluation pipelines for the system • Augmented pre-trained models for people re-identification process of tracking
Data Scientist
Customer segmentation for beauty retailer
PySpark ML
A data discovery project for a beauty retailer. The project was a collaboration work of data science and user experience teams. We have applied machine learning algorithms to big data. The results were a documented data science environment on Microsoft Azure full of data reports with valuable insights. Participation: • Created data loading and preparation pipelines for further analysis using PySpark. • Made a number of analytical lab reports based on transaction data. • Clustered customers using machine learning algorithms into segments using PySpark ML module. • Analyzed correlations between geographical data and customer behavior.
C++ Developer
Digital fashion mobile AR app
C++, Python
Mobile app powered by AR and deep learning / digital fitting room. A user can try new clothes or styles using only a smartphone. Participation: • Researched papers on related tasks solved via neural networks • Implemented model and pipeline for human pose estimation task • Realised cross-platform postprocessing library in C++, implemented Python binding for the library

Educational background

Languages

EnglishProficient