• Developed a real-time financial performance monitoring system using SQL for aggregating data from wide financial sources, efficiently tracking key metrics like revenue, expenses, and profit margins.• Utilized Pandas and Dask to handle and process vast financial datasets, over 1 million, using NumPy for numerical computations and Seaborn for statistical visualizations, providing deep insights into financial trends.• Designed SQL schemas by managing over 60 tables with 15 complex joins applying advanced normalization techniques to reduce data redundancy and enhance query performance.• Integrated financial data into Snowflake, handling up to 10 TB of data with AWS Glue for ETL and AWS Redshift for scalable warehousing, optimizing data processing and query performance for robust data management.• Developed machine-learning models using Scikit-Learn and TensorFlow, creating predictive models for financial forecasting and anomaly detection. Enhanced system accuracy in trend analysis and early issue detection.• Created interactive dashboards with Power BI, integrating data from 12+ sources creating 20+ dynamic visualizations with advanced filters and slicers, offering actionable insights and strategic decision-making.

• Developed and deployed 5+ interactive Power BI dashboards that tracked KPIs, analyzed clinical trial discrepancies, and identified operational inefficiencies, leading to a 20% reduction in costs.• Utilized Python (Pandas, NumPy, Scikit-learn) and AWS to analyze over 3 million rows of historical patient data, applying predictive modeling techniques to enhance treatment recommendations, ultimately improving the patient journey by 15%.• Streamlined data reporting workflows by automating processes with Python scripts (using libraries like OpenPyXL for Excel manipulation) and leveraging SQL for data extraction and transformation, enhancing accuracy and efficiency in patient data management.

• Automated data reporting and designed robust ETL processes using SQL and Python (Pandas, SQL Alchemy), delivering high-impact business intelligence reports for Merck stakeholders across the USA and Asia-Pacific.• Conducted detailed analyses on 2+ million rows of data across various metrics, developing comprehensive reports and Tableau dashboards that emphasized process-focused KPIs.• Enhanced log management and root cause analysis processes through Python automation (using libraries like Loguru), creating BI dashboards to monitor application performance and reducing production bug resolution time by 15%.• Collaborated in the implementation of change management strategies for new system rollouts and enhancements, ensuring effective stakeholder engagement and communication throughout the transition.• Supported the migration to the ServiceNow platform by drafting over 15 Knowledge Base articles, contributing to a 20% decrease in user ticket submissions through improved documentation.• Managed Active Directory using SQL for data integrity checks, for timely access provisioning and compliance with security policies.