Data Scientist

Directed cross-functional collaboration to transition international banking branches (New York, London, Dubai) into live production, streamlining workflows for 500+ employees and achieving a 20% boost in service delivery speed. Engaged in quantitative analysis and problem-solving initiatives, resulting in strategic insights that supported 3 major banking projects, optimizing existing trading strategies and contributing to a 15% reduction in operational costs. Designed and automated 15+ banking reports with tools like Oracle Analytics Server and BI Publisher, boosting data efficiency by 30%, reducing workload by 25% and enhancing decision-making.

Collaborated with business stakeholders to gather data pipeline supplies, defining ETL workflows and data models to process 10+ TB daily using Apache Spark (PySpark) & Hadoop HDFS, optimizing customer behavior analysis for 30% better targeting. Developed and optimized PySpark ETL scripts, easing transformation latency by 40% while ensuring 99.9% data accuracy via schema validation, deduplication, and cleansing, refining data consistency for downstream analytics and industry intelligence. Automated 1,000+ daily/hourly batch jobs using Apache Airflow, implementing failure recovery and retry mechanisms, reducing manual intervention by 90% and ensuring 99.5% on-time data availability for analytics and reporting teams. Optimized data storage and retrieval by implementing Hadoop HDFS partitioning & compression (Snappy, Gzip), cutting storage costs by 25% while improving read/write speeds, accelerating data processing for high-volume analytical workloads. Designed and maintained Apache Hive external tables, enabling petabyte-scale distributed SQL querying, reducing ad-hoc query execution time by 50%, and empowering business teams with structured, self-serve data insights for decision-making. Integrated Azure Data Lake Storage & Databricks, leveraging distributed computing, caching, and parallel processing to accelerate transformations by 3x, improving cloud-based data workflows, collaboration, and scalability. Implemented real-time monitoring and security using Apache Airflow UI & Log4j, reducing MTTR by 60% while enforcing SSL/TLS encryption & RBAC controls, ensuring compliance with enterprise security and data governance policies.