Ukraine's #1 job service
Андрій
AI engineer
- Considering positions:
- AI engineer, ML engineer
- City of residence:
- Lviv
- Ready to work:
- Remote
Contact information
The job seeker has provided: Phone number
Name, contacts and photo are only available to registered employers. To access the candidates' personal information, log in as an employer or sign up.
You can get this candidate's contact information from https://www.work.ua/resumes/20130478/
Uploaded file
Quick view
version
This resume is posted as a file. The quick view option may be worse than the original resume.
Andrii Lysun
Lviv, Ukraine | [open contact info ](look above in the "contact info" section) | [open contact info ](look above in the "contact info" section) GitHub: andriyqz | LinkedIn | Telegram: @andriyqz
EDUCATION
Lviv Polytechnic National UniversitySep 2025 — Present
BSc in Artificial Intelligence Systems (2nd Year Student)
TECHNICAL SKILLS
Languages:Python, SQL (PostgreSQL), Git
Machine Learning:XGBoost, PyTorch, Scikit-learn, Feature Engineering, Data Processing
Data Science:Pandas, NumPy, Matplotlib, Seaborn
Backend s DB:FastAPI, Pydantic, SQLAlchemy, PostgreSQL, REST API, Pytest
MLOps s DevOps:Docker, Apache Airflow, DVC, GitHub Actions, CI/CD, AWS
Generative AI & Architecture: LLM, RAG
AI Frameworks & Libraries: LangChain, Hugging Face
PROJECTS
Customer Churn Prediction (End-to-End MLOps)GitHub Repository
Automated churn risk assessment system for E-commerce platforms
• Model Development: Developed and optimized an XGBoost classifier to predict churn probability, categorizing customers into Low, Medium, and High risk levels.
• Backend Architecture: Built a robust FastAPI service with Pydantic validation and SQLAlchemy ORM, featuring a batch prediction endpoint (/predict_batch).
• Data Engineering: Designed a PostgreSQL schema to store customer statistics and historical prediction results, ensuring data integrity.
• Workflow Orchestration: Implemented Apache Airflow DAGs to automate daily batch processing (10,000 records/batch) with built-in fault tolerance and transaction rollbacks.
• Infrastructure: Containerized the entire ecosystem (API, DB, Airflow) using Docker Compose; implemented automated seeding for demonstration environments.
• Testing: Ensured system reliability with Pytest and FastAPI TestClient for integration testing.
Stack: Python 3.13, XGBoost, FastAPI, PostgreSQL, Airflow, Docker, Scikit-learn.
PERSONAL PROFILE
A highly motivated18-year-old developer specializing in Artificial Intelligence Systems.
Lviv, Ukraine | [
EDUCATION
Lviv Polytechnic National UniversitySep 2025 — Present
BSc in Artificial Intelligence Systems (2nd Year Student)
TECHNICAL SKILLS
Languages:Python, SQL (PostgreSQL), Git
Machine Learning:XGBoost, PyTorch, Scikit-learn, Feature Engineering, Data Processing
Data Science:Pandas, NumPy, Matplotlib, Seaborn
Backend s DB:FastAPI, Pydantic, SQLAlchemy, PostgreSQL, REST API, Pytest
MLOps s DevOps:Docker, Apache Airflow, DVC, GitHub Actions, CI/CD, AWS
Generative AI & Architecture: LLM, RAG
AI Frameworks & Libraries: LangChain, Hugging Face
PROJECTS
Customer Churn Prediction (End-to-End MLOps)GitHub Repository
Automated churn risk assessment system for E-commerce platforms
• Model Development: Developed and optimized an XGBoost classifier to predict churn probability, categorizing customers into Low, Medium, and High risk levels.
• Backend Architecture: Built a robust FastAPI service with Pydantic validation and SQLAlchemy ORM, featuring a batch prediction endpoint (/predict_batch).
• Data Engineering: Designed a PostgreSQL schema to store customer statistics and historical prediction results, ensuring data integrity.
• Workflow Orchestration: Implemented Apache Airflow DAGs to automate daily batch processing (10,000 records/batch) with built-in fault tolerance and transaction rollbacks.
• Infrastructure: Containerized the entire ecosystem (API, DB, Airflow) using Docker Compose; implemented automated seeding for demonstration environments.
• Testing: Ensured system reliability with Pytest and FastAPI TestClient for integration testing.
Stack: Python 3.13, XGBoost, FastAPI, PostgreSQL, Airflow, Docker, Scikit-learn.
PERSONAL PROFILE
A highly motivated18-year-old developer specializing in Artificial Intelligence Systems.
Similar candidates
-
Python, Java, AI Software engineer
Remote -
AI engineer
Remote -
AI-інженер
25000 UAH, Remote, Zhytomyr -
AI Automator
Remote, Kyiv, Other countries -
AI engineer
Remote, Zaporizhzhia -
AI Integration Engineer
Remote