• Developed and maintained MySQL databases for Credit Risk Monitoring, optimizing queries and ensuring data integrity for large-scale credit datasets, significantly improving database performance and reliability. • Utilized Python and NumPy to perform complex data analysis for Credit Risk Monitoring, creating efficient algorithms for data processing and statistical modeling, enhancing the accuracy and speed of credit risk insights. • Conducted data mining and cleansing operations on credit risk data, improving data quality and preparing datasets for analysis and reporting, thereby ensuring high-quality data for risk assessment and decision-making processes. • Created insightful visualizations and dashboards using Power BI and MS Excel for Credit Risk Monitoring, effectively communicating key risk findings to stakeholders and enabling data-driven decision-making, with dashboards viewed by over 10 key stakeholders. • Implemented version control best practices using Git, facilitating collaborative work and maintaining code integrity across multiple development efforts, which streamlined workflows and enhanced team productivity. • Analyzed campaign performance within Credit Risk Monitoring using knowledge of affiliate and social media marketing, providing data-driven recommendations for optimization, leading to improved risk management and ROI. • Demonstrated strong project management skills by coordinating efforts across teams, setting clear goals, and ensuring timely delivery of milestones, which contributed to the successful execution of credit risk monitoring projects. • Fostered effective communication and collaboration with stakeholders, leveraging interpersonal skills to build strong relationships and ensure alignment on project objectives and deliverables. • Exhibited critical thinking and problem-solving abilities by addressing complex challenges in credit risk monitoring, providing innovative solutions that enhanced overall risk management processes.

•Provided comprehensive application support for the trading floor, utilizing ION and UNIX systems to manage and troubleshoot issues, ensuring minimal downtime and enhanced trading efficiency. •Conducted regular checks on weekly Treasury securities, collaborating with financial analysts to verify and update information in the ION database, maintaining the integrity of financial records for 100 securities. •Managed and executed updates for multiple components and servers within the ION system, coordinating with IT teams to implement changes while minimizing disruptions to trading activities. •Engaged in data wrangling and warehousing activities, organizing large datasets and employing various transformation techniques to prepare data for reporting and analysis. •Performed routine maintenance and troubleshooting for the ION system and NoSQL databases, responding to alerts and resolving issues to ensure optimal performance and reliability of trading operations, handling 50+ maintenance tasks month. •Utilized Matplotlib library to create visual representations of financial data, developing charts and graphs to present complex information in an understandable format for analysis and decision-making processes.•Created comprehensive, interactive dashboards and reports in Power BI, translating intricate financial data patterns into visually compelling presentations that drove strategic decision-making.•Implemented data cleaning and data governance practices, ensuring data accuracy, consistency, and compliance with industry standards for critical trading and financial datasets.

•Analyzed complex datasets using Python and SQL, extracting actionable insights that drove significant increases in marketing campaign effectiveness and supported data-driven decision-making across departments.•Designed and maintained Oracle databases, implementing efficient data storage solutions that improved query performance and ensured data integrity across multiple systems.•Leveraged the Pandas library to clean, transform, and manipulate large-scale datasets, reducing data preparation time by 150 hours annually and significantly improving analysis accuracy.•Developed interactive dashboards and reports using Tableau, effectively visualizing key performance indicators (KPIs) that led to increased stakeholder engagement and understanding.•Architected and implemented data pipelines on AWS, utilizing EC2 and S3 to automate data workflows, resulting in substantial reduction in manual data processing time and enhanced scalability of analytics operations.•Conducted advanced statistical analyses to identify trends, patterns, and correlations in customer behavior, contributing to improvements in customer segmentation and personalized marketing strategies.•Collaborated with cross-functional teams using Agile methodologies, delivering data-driven solutions that optimized email marketing campaigns and increased open rates through improved targeting and content personalization.•Managed version control using Git, ensuring proper documentation and tracking of code changes, which facilitated seamless collaboration among team members and reduced code conflicts in collaborative data analysis projects involving 10 contributors.