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Резюме от 21 мая 2024 Файл

Dmytro

Python-програміст

Возраст:
20 лет
Город:
Киев

Контактная информация

Соискатель указал телефон , эл. почту и LinkedIn.

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Ukraine Dmytro Khomych GitHub LinkedIn
Kyiv [открыть контакты](см. выше в блоке «контактная информация»)

Technical Skills

Python, Django, DRF, FastAPI Pandas, NumPy, MatPlotLib, async libraries, OpenAI, LangChain,
SQL(PostgreSQL), NoSQL(MongoDB), AWS(EC2, EC2 P4, S3), Docker

Summary
• 3+ years of experience in software development with a focus on Python and its libraries;
• Skilled in backend development and deployment, creating robust and scalable systems;
• Proficient in SQL and NoSQL databases, including design and management;
• Experienced in AI integration and data processing using machine learning frameworks;
• Strong project management skills in gathering requirements and estimating timelines;
• Fluent in English (C1 level) with excellent communication skills.

Experience
Boosty (Jan 2024 – Present)
Stack: FastAPI, asyncio, httpx, aioboto3, poetry
“Optimize the application and improve its asynchronous capabilities”
Responsibilities:
- Refactored endpoints for asynchronous operation using asyncio
- Developed an asynchronous HTTP client with httpx
- Implement aioboto3 client for S3 interaction
- Transitioned package management from pip to poetry
- Enhanced documentation and improved application stability

NutritionApp (Jul 2023 – Jan 2024)
Stack: Stable Diffusion, FastAPI, MongoDB, EC2, EC2 P4, S3, Sentry, Locust, asyncio,
aioboto3
“Develop an application providing optimal recipes for women's well-being”
Responsibilities:
- Set up Stable Diffusion image generator on EC2 P4
- Developed and deployed FastAPI-based API on EC2
- Integrated S3 for image storage from the generator
- Refactored code for asynchronous operation with asyncio and aioboto3
- Integrated OpenAI for recipe generation
- Conducted load testing with Locust and monitored performance with Sentry
- Connected MongoDB for user data storage

WeShyft & Uvocorp (2022 – 2023)
Stack: FastAPI, Pandas, PostgreSQL, AWS, Docker, Xano, TensorFlow, PyTorch
“Implement new features, process existing data, and utilize AI assistance”
Responsibilities:
- Integrated Google BigQuery and PostgreSQL for data storage
- Designed project structure and database on Xano
- Processed and reassembled data using Pandas and NumPy
- Deployed APIs in Docker to AWS servers
- Developed asynchronous APIs with FastAPI
- Implemented AI logic using TensorFlow and PyTorch

Freelance (2021 – 2022)
AI Q&A assistant
Stack: LangChain, FastAPI, ChromaDB, black, isort, Docker, AWS
“Enable document uploads and AI-based Q&A using provided data”
Responsibilities:
- Developed AI logic with LangChain and ChromaDB for document-based answers
- Standardized code quality using black and isort
- Deployed the application with Docker on AWS

Data analysis of war
Stack: Pandas, NumPy, SciPy, MatPlotLib, Scikit…
“Detect correlations on the battlefield for future use”
Responsibilities:
- Processed data using Pandas and NumPy
- Visualized data and detected errors with Matplotlib
- Applied data analysis algorithms using SciPy and Scikit

Anonym board
Stack: Django, DRF, PostgreSQL, JWT
“Create a platform similar to Reddit or 4chan for thread creation and messaging“
Responsibilities:
- Developed APIs with Django Rest Framework
- Implemented JWT authentication for security
- Designed and managed PostgreSQL database structure

Binance trade app
Stack: Django, DRF, PostgreSQL, Docker, AWS
“Test trading algorithms on historical or real-time data”
Responsibilities:
- Created base trading strategies
- Developed user interactions with Binance via FastAPI
- Processed historical trading data using Pandas
- Designed PostgreSQL database for user and market data storage

Education
Taras Shevchenko National University of Kyiv (2021 – Present)
Faculty of Computer Science and Cybernetics

Kyiv College of Communication (2019 – 2021)
Faculty of Computer Systems and Networks

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