At Vector ML Analytics, I develop automated financial-data pipelines using Python, AWS, and PySpark. I optimized distributed ETL processing across AWS Glue, Amazon S3, and Amazon RDS, improving pipeline efficiency by 20%.
I also migrated the Loan Amortization ETL project to an AWS Lambda-based architecture orchestrated with AWS Step Functions, reducing execution time by 80%. My work includes building data-processing workflows and APIs with FastAPI, and collaborating with Finance teams and end clients to translate requirements into data engineering solutions.
As a Data Science Intern at Transloom, I deployed translation APIs using FastAPI and open-source models, achieving over 90% accuracy. I also worked on image and document translation using OCR and PIL, and built a student-performance data pipeline that processed and analyzed examination results.
