Viktor Andriichuk

Solo Entrepreneur | LLM and Python Expert | Big experience in hands-on Python, Data, ML, LLM, DevOps

Skills (experienced since the 2017):

Programming languages

Python (primary language)

Data Bases, Data Warehouses

Neo4J, PostgreSQL, MongoDB, Redis

Frameworks

FastAPI, Flask, Django, LangChain, LangGraph, LlamaIndex

Messages Brokers

Kafka, RabbitMQ

Tools

Docker, Celery

Data Science

Classical ML, LLM, NLP

Links:

My brands:

Gazolin Production (micro SaaS), DataFlux (Outsourcing, Outstaff), Agents of Fortune (AI SaaS),

Social media

Linkedin, Facebook, Twitter, Github

Blogs

Habr, AI Agents Blog YouTube

Courses and Certificates

EPAM Big Data Masters Program, Construction of asynchronous additions on Python (Course), Apache Spark (Course), Big Data (Course), Scala for Java Developers (Course), Go! (Course), Data Engineer: from middle to expert (Course), NLP (Course), English for IT (Course), Data Science Accelerator (Course), Data Science Specialization (Course), Practical course for beginners in SQL and PostgreSQL (Course), Docker and Docker Compose: from Zero to Hero (Course), The Complete Guide to Python 3: From Beginner to Expert (Course)

Career:

Curriculum Vitae (CV)

Team and Tech Lead Python and LLM Engineers Team
@GartTech

Under my leadership the technical team created an updated core product of the platform, which accelerated the development of client bots by 40 times and also reduced the cost of such a bot by 80 times.

Python Backend Software Engineer
@HotCode

While working on the CRM for internal use in the company, I implemented the LLM so that users using natural language could manage various processes in the CRM. As a result, this increased employee engagement in working with SRM by 50% and also reduced time spent on routine tasks

Python Backend Software Engineer
@ASICS DIGITAL

I communicated closely with the project stakeholders to collect requirements, designed a data collection and storage system, and quickly developed this system for parsing data for many coins, storing it in Mongo and bringing it to production. This allowed the stakeholders to attract investment.

Python Backend Software Engineer, DevOps
@Fabiosa Media

Data Platform for Insights for Fabiosa Media - the top #4 Facebook media publisher in the world:

I created a platform where businesses can find insights into their data and build dashboards and recommendations from Gen AI. It helps to decrease the time for making decisions.

Team Lead / Python Full Stack Softsare Engineer / Data Scientist
@Video Auto Translator

Application Tech Design & Architect.
Tuning Machine Learning Models.
Collect Data for ML Models.
Developing Back-End.
Team Leading.

Python Software Engineer
@HEALTH UNION

A network of sites for health care:

While working at the company, I actively created internal frameworks for integration with Apache Airflow, monitoring data quality and testing analysts' SQL scripts. By using pytest during the development process, I ensured our code's high stability and reliability while speeding up the verification and bug-fixing processes.
I developed a service that interacts with networking sites where users express opinions on health topics. The main task of the service was to search for spam among comments and generate content recommendations for the user. To implement this task, I used FastAPI and models created by our data scientists. To increase the efficiency and speed of the system, I actively applied optimisation algorithms and integrated the numpy library into the data processing process.

Python Developer
@Analitycs Dashboards

As part of my project, I collected data from many different sources. Using Python combined with AWS Lambda Functions, I automated the process of retrieving information from the API and storing the data in AWS S3. After the aggregation phase, I initiated ETL processes using AWS Glue to process and structure the resulting information. Then, using AWS Athena, I created a data mart, based on which analytical dashboards were built in AWS Quicksight. These dashboards have become a valuable tool for management, providing deep analytical insight into the data collected.

Data Scientist / Python Softsare Engineer
@BSG.WORLD

SMS-, Email sender:

AntiSpam Machine: As a Python and machine learning developer for BSG, I built an AntiSpam microservice for a marketing platform using FastAPI, MongoDB, Redis and machine learning algorithms. In addition, a microservice was developed to control the operation of AntiSpam./span>
Data Lake and DWH: As a Python Back-end Developer and Data Engineer for BSG, I built a data warehouse from scratch and developed ETL pipelines to store data from online stores in the Data Lake in real- time.
Recommendation System: As a Python developer and data scientist at BSG, I developed a recommendation engine using machine learning algorithms and created a microservice for an online store's recommendation system in Flask.
Chat-bot: As a Python developer for BSG, I created a chatbot solution Telegram and Facebook Messenger.

Data Scientist / Python Software Engineer
@LEKOS

System Design.
Full-stack developed reccomendation system as a product for e-shops.

  1. Education

    Taras Schevchenko National University of Kyiv

    Finance, Bachelor
    1998 - 2003

  2. National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

    Applied mathematics, Master's degree
    2020 - 2021

  3. Kharkiv National University of Radio Electronics

    Data Science, Master's degree
    2022 - 2023

  4. EPAM Big Data Masters Program

    BigData
    2022 - 2023