- Aggregated, normalized, and analyzed enterprise IT vulnerability data, developing Tableau and Power BI dashboards to support leadership in prioritizing remediation efforts and ensuring regulatory compliance.- Built data pipelines in Python to automate data extraction and transformation from online sources, improving data accessibility for end users and saving over 40 hours of operational time weekly.- Designed and implemented a Fabric Cloud Data Warehouse with a structured Bronze, Silver, and Gold layer architecture, enabling advanced analytics and data optimization across multiple business functions.- Conducted exploratory data analysis to optimize Power BI dashboards, enhancing dashboard performance, reliability, and customization for executive reporting.- Utilized Python to integrate company reports via API, streamlining data extraction and loading into Azure SQL Database. Transformed and normalized the data to improve accessibility for end users and support advanced analytics.

- Led the implementation of a data transformation initiative using Apache Airflow, DBT, Snowflake, and Sigma, optimizing data processing and analytics workflows. Drove the project from conception through completion, coordinating with cross-functional teams to ensure alignment with strategic business objectives.- Identified high-risk characteristics in loans, credit cards, and credit lines to develop operational risk assessment reports, reducing the time required to detect at-risk accounts by 70%.- Developed a 5-year forecast model for Adjustable-Rate Mortgage (ARM) loans approaching rate adjustments, evaluating borrowers' post-adjustment payment capacity. Leveraged insights to identify potential default risks, enabling proactive planning and risk mitigation strategies for the bank in anticipation of borrower repayment challenges.- Employed SQL and Python to process and analyze large datasets, performing data cleaning, aggregation, and summarization to support various data analysis tasks.- Designed interactive dashboards and visualizations using Power BI, SQL Server Reporting Services, and Sigma to present insights to business stakeholders, facilitating data-driven decision-making across teams.

- Conducted research and analysis to record data and examine differences between soil samples.- Interpreted data analysis results via Microsoft Excel to draw inferences and conclusions about whether or not the soil samples were affected by different fertilizers.- Helped to determine if a new type of fertilizer would be effective or detrimental for golf course putting greens year-round.

- Prepared individual, trust, partnership, and corporate tax returns.- Utilized tax-related software such as CCH Axcess to prepare and process returns and research tax matters.- Used Microsoft Excel to input and track tax information.- Surpassed expectations to achieve an extension with the internship program.