Key Skills

Freelancer Overview

I have a strong foundation in data engineering, backend systems, and AI-driven analytics, with hands-on experience in building scalable data pipelines and ensuring data quality for downstream analytics and machine learning. My work as a Data Scientist Intern involved developing high-throughput event ingestion backends using Python, FastAPI, Kafka, and ClickHouse, where I optimized data completeness and query performance—critical for accurate AI model training and annotation workflows. I am skilled in designing reliable systems that maintain data integrity, handle concurrency, and support large-scale data processing, leveraging tools like Redis, PostgreSQL, and RabbitMQ. My academic background in mathematics and computer science, combined with published research in reinforcement learning, graph neural networks, and AI model optimization, enables me to approach data labeling and annotation tasks with both technical rigor and a deep understanding of AI model requirements. I am passionate about ensuring the accuracy and reliability of training data to support robust AI solutions.

Labeling Experience

Education

Work History