Hassan Salahuddin

1. Built an end-to-end ETL pipeline with Apache Spark to enhance large-scale data processing 2. Migrated data flows from SSIS to Spark & Airflow, increasing system performance and scalability 3. Maintained Azure Data Factory pipelines for cross-platform data transfers 4. Conducted Snowflake schema design and data modeling for analytics 5. Wrote PyTest test cases with >90% code coverage to ensure pipeline reliability 6. Monitored and optimized SSIS pipelines for seamless data flow

1. Developed ML solutions for emergency medical case classification and patient risk assessment. 2. Handled class imbalance with advanced sampling techniques to improve prediction robustness. 3. Achieved 90%+ accuracy in Body System Risk Prediction using custom NLP pipelines. 4. Delivered insights through BI tools (Excel, Power BI) with tailored visualizations. 5. Applied XGBoost and deep learning methods to derive actionable healthcare insights.

Currently pursuing a Master’s degree focused on advanced data science techniques including big data analytics, machine learning, statistical modeling, and data engineering pipelines. The program emphasizes both theoretical foundations and practical applications across cloud platforms and large-scale data systems.

Graduated with distinction, awarded the Dean’s List honors (2020, 2021, 2023) and a Bronze Medal in the final semester. Coursework included Artificial Intelligence, Computer Vision, Databases, Web Development, Software Testing, Data Structures, Algorithms, and Operating Systems. Gained a strong foundation in programming, software engineering, and applied machine learning.