Amir Ayat

Maintained and optimized high-throughput data pipelines processing approximately 2 billion records per day from network elements. Designed and orchestrated ETL workflows using Apache Airflow and ClickHouse for large-scale analytical workloads.

Founded and developed Relocate.works, a smart job discovery platform. Built a full-stack web application using Django and AWS, integrating Generative AI to analyze job descriptions for relocation and visa benefits.

Led the design and deployment of an Azure Data Lakehouse, integrating ADLS Gen2, Databricks, and Synapse Analytics. Developed ETL/ELT pipelines using Azure Data Factory, PySpark, and SQL, improving data availability by 40%.

Implemented a scalable membership system on AWS integrated with Stripe, enabling various billing models. Developed data pipelines and optimized database performance, reducing costs and improving response times.

Collected social media data using Selenium and Beautiful Soup, transforming and loading it into a data lake. Developed an analytical dashboard with FastAPI and improved performance by preprocessing data, achieving 5x faster response times.

Built AI-powered algorithmic trading bots and developed a RESTful web API for customer interaction. Created a back-testing module for the AI team, reducing testing time and increasing accuracy by 10%.

Deployed a data pipeline to collect cryptocurrency news, OHLCV prices, and on-chain data into a data lake. Implemented data validation and cleaning processes, increasing data validity by 5% and enhancing AI model performance.

Applied QA methodologies to assess web application performance and security. Implemented database security measures and optimized database queries, achieving a 3x improvement in site loading speed.

Pursuing a Master of Science in Artificial Intelligence in Computer Science, expected to continue beyond the current date.

Earned a Bachelor's degree in Computer Science from K. N. Toosi University of Technology from 2014 to 2018.