Currently, I’m a Team Lead and Machine Learning Engineer. I can organize the Machine Learning process end-to-end and bootstrap the work of the Data Science Team.
I’m business-oriented and focused on problem-solving, not just implement a technical solution. I’m excited about building new products and I have the strong technical knowledge to build complex AI-driven solutions. I’m interested in having a strong connection with business goals.
I primarily worked with Java and Python stack and I can learn any new technologies when it is needed, I had wide experience with search engines (solr, elasticsearch), NLP frameworks (NLTK, Spacy, Stanza) Machine Learning frameworks (tensorflow, keras, sklearn) and dozen of other things.
My hobby is developing pet-projects and products, I tried several times to organize my own company and launched some products on the local market. Also, I’m looking for a business mentor, from my side I can be useful to advise about cutting-edge technologies.
Industries I have special experience with:
Legal & Regulatory, Financial, Entertainment, Information Retrieval
Machine Learning: NLP, Sklearn, Keras, Tensorflow, Gensim, Computer Vision, Data Analytics, Math,
Software Engineering: Python, Flask, Java, Spring Boot, JUnit, pytest, REST, Jena
Databases: MongoDb, MySQL, MS SQL Server, Graph Databases
Team Management: Scrum, Kanban, SAFe, Jira, trello
Environment: Docker, Linux, Bamboo CI, Gitlab CI
Search Engines: Elasticsearch, Solr, Lucine
Architecture: Component diagrams, Sequence diagrams, UML, technical documentation
Time: Feb-2019 — Now
Team size: 20+
Summary: Product goals to provide an advanced exploratory search for layers and provide analytics based on the case history. The product is oriented to several EU markets and included a lot of state-of-the-art machine learning research.
Time: Sep-2018 — Jun 2019
I was a contributor and main instructor of course: Fundamentals of Intelligent Data Analysis. I was conducting lectures and exercises.
The course contains several sides of Data Mining focused mostly on Natural Language Processing.
Besides, I was an instructor for a diploma, my students successfully defended their works.
Time: Jul-2018 — Feb-2019
Team size: 5
Summary: This period of works includes AI-related activity which includes many projects and POCs.
Time: Jul, 2017 — Now
Team size: 6
Summary: Product for small and near to the middle retail businesses which provide:
The project had several pivots and finally, we came up with implementing CRM with personal analytics for small businesses. We provide a simple solution when business owners can integrate our product in several minutes and start using it. We will provide fulfill information about the client base and transaction history, also simplify communications with clients and we do advanced analytics on demand. MAU: 3K
For this project we used the many technologies, we had react.js apps and mobile applications implemented in swift and kotlin with backend implemented in java. The current version is pure python and web applications implemented in vue.js.
Product Analytics, Architecture, Backend Implementation, OPS, Project Management
Flask, Reactjs, Kotlin, Swift, JUnit, Python, Vue.js, Linux, Docker, pytest, gitlab ci, Docker/docker-compose, git, maven, Gitlab CI, bash, trello, miro, notion, MongoDb, java 8, Spring Boot, Loki, grafana
Time: Oct-2016 - Jun-2018
Team size: 8
Summary: Content Delivery Chanel intended to perform batch processing of the content and metadata and deliver content to the search engine. This project includes several sub-systems: managing environment configurations, service for managing Table of Content.
Elasticsearch, graph databases, jena-tdb, jboss fuse, tomcat, apache fuseki, ELK, kibana, sonar, findbug, pmd, checkstyle, pmd, winscp, bamboo ci, git, jira, maven, ant linux, cron, java 7, Java EE, activemq, spring 3, REST, SOAP, tomcat, jboss fuse, jena, xslt, RDF, xml, xpath, semantic web, junit, cucumber, camel, blueprint, sparql, log4j, lombok
Time: Oct, 2015 — Sep, 2016
Team size: 8
Summary: B2B Pharmacy Consultant: This product was developed to solve several problems:
Retrospective analysis: We did quite well to translate complex business requirements to an elegant design, implemented simple UX at the same time we did nice technical solutions to support many business requirements with a simple scalable design. We had a lack of business experience and our communication with customers and go-to-market strategy wasn’t so good. Finally, the project was closed because of growth challenges.
Technical Description: Backend implemented with spring boot. Admin panel developed with AngularJS. Docker was used for project deployment. Nginx used as a proxy. We also actively used an analytics system to collect user behavior and recognize patterns to detect UX problems and evaluate the usefulness of features.
The project includes various components:
Responsibilities: Technical Leader — SDLC process organization, code quality control, configured CI/CD, automatization. Backend developer — implementation search system including fuzzy matching, ranking, and search by anthology graph. Also developed a recommendation system based on rules. OPS, configuration servers, proxies, deployment management.
Technologies: Java 8, Spring MVC, Spring Security, Spring Data, Spring Boot, JSP, For admin-panel was used AngularJS. JPA/Hibernate, QueryDSL, Linux, Docker, JUnit / Spring Test Framework, docker-compose, git, Gradle, maven, Gitlab CI, Jenkins CI, bash, Python for data processing and aggregating from different sources, trello/gitlab issue tracker, Fiddler, MySQL (Used JPA/Hibernate, Spring Data)
Jun 2015 — Oct 2016
I was responsible to develop a course to teach programming in java from scratch and conducting training lessons. The course program contained 2 sections: basic Java and Java EE. For the final project, students were implementing web applications that interact with the database and have authorization. I had good student retention and more then half of the students got jobs in the IT industry. I had 4 groups, different aged audience.
Time: 2015 — 2016
Team size: 2
Summary: Aggregation service for collecting advertisements for long-term rent. Our service collects advertisements, deduplicates and normalizes them. Provides search with ranking, filtering, and sorting results.
Retrospective analysis: When we started this project we focused mostly on the technical side and loosed important product and marketing questions. Unfortunately, you can’t create a product without talking with clients. We didn’t know a lot about Product Management.
Technical Description: We had implemented with spring backend and react.js app for UI. Google Analytics and tag manager were used. As data storage was used MongoDb, deployed in PaaS OpenShift then migrated to cloud service and Docker.
The project includes various components:
Responsibilities: Architecture, Backend Implementation, OPS, Product / Project Management
Technologies: Java, Spring boot, React.js, OpenShift, maven, git, jsoup, ODM morphia, docker, docker-compose, Linux
Aug-2014 — Aug-2016
During my work at the university, I contributed to nearly all courses in our department:
Essentially I was helping with courses:
I am actively participating in many activities aimed at growing people, I am glad to help motivated people to develop in the IT-field, I joy to see your shining eyes.
Therefore, I am happy to take part as a participant or organizer for meetups, conferences, hackathons. I open to consultations about any related to my experience topics.
I’m leading the local community, about data science and data mining. Currently, more than 100 people gather for irregular meetups (https://t.me/ds_gomel_chat ). Besides, I’m cooperating with other city-level communities. I regularly have a technical talk.
I play the role of a trainer and advisor for different disciplines: Java, Python, Machine Learning. Involved in mentoring activities.
I am participating as a consultant for the university and training centers. I’m open to being invited to speak at the university about the current state of the IT industry and related to me topics.
Department: 05.13.05 Elements and devices of computer technology and control systems
Time: 2016 — 2020
Research domain: computer vision, object detection, vehicles tracking, traffic-light management, optimization
Summary: I was focused on the integration of intellectual analytics and monitoring systems of road traffic. My research was concentrated on extraction information from the video stream and building optimization models to reduce traffic-load. I was working on optimization models to be deployed on raspberry pi v3 and similar single board computers.
Systems as I worked on could be used as a supplementary component to tune already existing imitation models to correct traffic-light regimes.
Stretch goal: A city where all roads and traffic-lights know information about road situations every single moment, the system could dynamically change traffic lights regimes to normalize traffic. It is exciting, is not?
Department: Mathematical modeling, numerical methods and program complexes
Time: 2014 — 2016
Diploma score: 10 (from 10)
Summary: There is a continuation of my bachelor’s work. I researched dynamic transients processes modeling with the finite element method.
Main components of developed modeling application:
Department: Computer Engineering and Design
Time: 2014 — 2016
Diploma score: 5 (from 5)
Summary: I learned various approaches on how to design web applications, to works with vector and raster graphics. As a final project, I implemented a 3D web editor using WebGL (Three.js) and angular.js. As a result, this editor was used for other projects dedicated to mathematical modeling.
Department: Information Technology
Time: 2009 — 2014
Diploma score: 10 **(from 10)
Summary: During student years I had research experience, participated in several conferences, and presented thesis’s related to my final project.
My final project was related to transients processes modeling. This project includes two parts:
### School of management by Yandex (Мобилизация» 2017) (self-education)
### Scientific Thinking
### Introduction in Machine Learning (Yandex, SHE)
### Основы Angular 2
### Developing Innovative Ideas for New Companies: The First Step in Entrepreneurship (University of Maryland)
### Developing web services in Java (part 1)
### Developing web services in java (part 2)
### Machine Learning
### Getting and Cleaning Data (john hopkins university)
### M101P: MongoDB for Python Developers
### M101J: MongoDB for Java Developers
### edX Honor Code Certificate for Scalable Machine Learning with Spark
### Data Science foundations using R (john hopkins university)
### Линейная алгебра (Linear Algebra) (SHE)
### The Data Scientist’s Toolbox
### Programming Mobile Applications for Android Handheld Systems: Part 1 (University of Maryland)
### Programming in Java and Java EE by Yakov Fain
### Scalable Microservices with Kubernetes