Rasheed Khan Email & Phone Number

Baltimore, Maryland, United States

Designed and implemented resilient data pipelines for finance portfolio management using PySpark, Apache Airflow,Azure Data Factory, Azure Functions, and Apache Spark for seamless ETL processes with large financial datasets.Managed data storage management within the financial sector, optimizing performance and maintaining data integrityusing Azure Data Lake and PostgreSQL, tailored specifically to portfolio management requirements.Worked on real-time data processing initiatives, employing PySpark Streaming and Kafka Streams to analyze highvolume financial data streams, enabling timely risk mitigation strategies within the portfolio management framework.Utilized advanced data analysis and machine learning techniques with Python libraries such as Pandas and NumPy toextract actionable insights from financial data, supporting strategic decision-making in portfolio management.Developed interactive dashboards using Power BI and crafted custom visualizations with Matplotlib to effectivelycommunicate critical findings and trends to stakeholders in the finance risk management domain.

Hyderabad, Telangana, India

Developed and implemented machine learning models using Python, including Decision Trees and Text Analytics, whichresulted in a 15% improvement in model accuracy and provided more reliable predictive insights.Streamlined ETL processes by optimizing Apache Spark jobs through advanced statistical modeling and Python libraries,achieving a 30% reduction in claim cycle time and significantly enhancing data processing efficiency.Architected a scalable data infrastructure that integrated AWS Redshift, Snowflake, Apache Kafka, and Airflow,automating data pipelines and workflows, resulting in a 40% reduction in data retrieval times and improved overall dataflow management.Utilized SQL to design and query complex datasets within data warehouses, enabling comprehensive data analysis andfacilitating faster decision-making processes.Leveraged Python and AWS visualization Quick sight to analyze customer behavior and market trends, resulting in a 40%increase in sales conversion rates within the targeted demographic. Collaborated with stakeholders to gather requirements and translate feedback into actionable reports using Python andSQL, automating reporting tasks and reducing manual work by 40 hours per month