salmaff

1. Designed and managed 70+ fact and dimension tables using star schema as the core enterprise Data Warehouse architecture. 2. Built end-to-end automated ETL and data ingestion pipelines with Python, Apache Hop, and SQL, integrating data from 10+ heterogeneous sources including REST APIs, PostgreSQL, ClickHouse, BigQuery, CSV/Excel, and web data. 3. Developed Python-based web scraping and external API workflows using Requests, BeautifulSoup, and Selenium to collect, validate, enrich, and integrate structured datasets into the enterprise Data Warehouse. 4. Developed and optimized 60+ complex SQL queries powering 15+ dashboards for institutional and product analytics. 5. Conducted product performance and adoption analytics using BigQuery, analyzing feature usage, user behavior, engagement, and adoption metrics. 6. Monitored ETL pipelines through Jenkins CI/CD and ClickHouse ingestion, maintaining 99%+ data reliability. Collaborated across analytics, product, and engineering teams to translate business requirements into scalable data solutions.

1. Co-authored scientific journal papers on biomedical AI, contributing to methodology, experiments, and result interpretation. 2. Labeled and preprocessed 10K+ medical images and biosignals (e.g., ECG) for deep learning. 3. Built classification models with PyTorch, achieving up to 80%+ accuracy on biomedical image tasks. 4. Converted biosignals into image formats for vision-based modeling. Developed GAN-based augmentation pipelines, boosting dataset size by 50% and model F1-score by 12%. 5. Led end-to-end AI tasks across 3+ research projects, from data prep to deployment.