Position: Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 3

- Led the development of a GAN model for floor plans, resulting in realistic and diverse floor plan layouts.

- Increased company revenue by 15% through the automation of critical business processes using custom DS/ML technologies.

- Designed and implemented a Super Resolution model to upscale low-resolution images, improving the quality of visuals for customers.

- Proficient in Python, AWS, Pytorch, OpenCV, PostgreSQL, Gitlab CI/CD, Docker, k8s, MLFlow, xgboost, and other cutting-edge technologies.

- Analyzed borrower profiles, optimizing lending strategies with data-driven insights.

- Formulated and maintained a hypothesis-driven approach for personalized client recommendations, resulting in increased satisfaction and loyalty.

- Led the development of the SuperApp Recommendation System, driving innovation and growth with business logic and architecture.

- Won the 1st place in Datathon with project for UNICEF.
In my previous experiences (3 years), I have completed various projects and tasks utilizing cutting-edge technologies such as Python, AWS, Pytorch, OpenCV, PostgreSQL, Gitlab CI/CD, Docker, k8s, MLFlow, and xgboost. I strive to continuously improve my skills and stay up-to-date with the latest industry trends to deliver high-quality results in any ML-related role I take on.
Interesting projects. Currently keen on NLU/NLP and CV tasks 🫶