● Data Science: Participated in all stages of data analysis: discussing the task with partners, collecting primary data, generating additional data, selecting models,● Machine Learning Engineering: Executed model training (mostly LLMs. By various fine-tuning methods), constructed pipelines, and optimized model performance using various frameworks and techniques.● DevOps: Utilized Docker for containerizing applications.● Backend Engineering: Leveraged a variety of frameworks (such as FastAPI, Django, and Streamlit) for backend model implementation.

● Data Science part: data analysis, risk identification, predictive modeling, and optimization of financial risk management strategies● Backend development part: Python software development for automation of actuarial calculations in accordance with IFRS standards (cash flow generator), scripting in Python● Conducted an actuarial audit of companies: checking and calculating reserves for liabilities, assessing future insurance reserves. Participated in the development of a system for automating actuarial calculations.

Developed and maintained a model to improve video quality.