Technical Skills
Portfolio
Featured Projects & Tools
For 26 years, I dedicated my career to financial analysis, data-driven decision-making, and technological innovation at the Federal Deposit Insurance Corporation (FDIC). Throughout my tenure, I developed numerous tools to automate financial assessments, streamline workflows, and enhance data visualization for key stakeholders.
Due to the proprietary nature of my work, I am unable to share the exact tools I created. However, I can provide detailed descriptions of my projects, highlighting how I leveraged financial analysis, data analytics, automation, and visualization tools to address complex challenges in the banking and economic sectors. My work combined multiple technologies—including Tableau, Power BI, R, Python, VBA, and SAS—to develop custom solutions that empowered analysts and decision-makers with the insights they needed.
Purpose:
This automated tool was designed to help financial analysts and regulators track stock prices across financial institutions. It provided users with an intuitive way to compare stock performance against relevant market indexes, create and analyze custom portfolios, and quickly investigate price movements.
One of the standout features of this tool was its automated search functionality, which allowed users to instantly retrieve market news and updates that could explain sudden price fluctuations. By integrating real-time data retrieval and visualization, this solution helped decision-makers stay informed without needing to manually collect and analyze stock market data.
Technologies Used:
- Tableau – Designed interactive dashboards for visualizing stock performance.
- Microsoft Task Scheduler (MTS) – Automated the process of opening Excel and Tableau Prep for scheduled data updates.
- Microsoft Excel (VBA) – Utilized a vendor’s Excel Add-In to automatically download stock price data, process it using VBA scripts, and save the updated dataset.
- Tableau Prep Builder – Cleaned and transformed raw stock price data for seamless ingestion into Tableau.
- Tableau Server – Hosted and refreshed dashboards to ensure users accessed the most up-to-date stock data.
Impact:
- Increased efficiency by eliminating the need for manual stock price tracking.
- Allowed users to create customized watchlists and monitor changes over multiple time frames.
- Integrated real-time search links, reducing the time spent investigating price fluctuations.
Purpose:
This dashboard provided a comprehensive view of economic conditions at multiple geographic levels—state, metropolitan area, and county. Designed to be an automated, data-rich resource, it allowed users to quickly analyze key economic indicators such as employment rates, GDP growth, consumer spending trends, and housing market conditions.
By leveraging automation, the dashboard ensured that users always had access to the latest economic data without manual updates. It was particularly valuable for economists, policy analysts, and financial regulators who needed to monitor regional economic trends.
Technologies Used:
- Tableau – Designed an interactive interface that enabled users to drill down into specific geographic regions and explore economic indicators in real time.
- R / R Studio – Utilized an API to pull economic data from external vendors, process the information, and convert it into a Tableau-friendly CSV format.
- Proprietary Task Scheduler – Automated the entire update process, ensuring that the dashboard was refreshed daily with the latest data.
Impact:
- Provided instant insights into regional economic performance.
- Eliminated the need for manual data gathering, allowing analysts to focus on interpreting trends instead of managing data.
- Enabled policymakers and decision-makers to identify emerging economic risks at a granular level.
Purpose:
The commercial real estate market is a vital component of the broader economy, and this tool provided users with real-time data on market trends across industrial, multifamily, office, and retail properties. Designed with a focus on user-friendliness, this solution allowed financial analysts to quickly assess key market indicators, including:
- Vacancy rates
- Market capitalization
- Availability rates
Users could filter and rank metro areas based on various financial and real estate metrics, making it easier to spot emerging market opportunities and risks.
Technologies Used:
- Power BI – Created an interactive platform for real estate data exploration and analysis.
- Python / Spyder – Developed scripts to retrieve and integrate data from multiple sources, including internal banking data and vendor APIs.
- Power BI Service – Automated dataset updates and ensured that the tool was available across the organization via a centralized app.
Impact:
- Provided an accessible, data-driven approach to real estate market monitoring.
- Allowed decision-makers to evaluate the financial stability of different commercial property sectors.
- Ensured timely and accurate insights through automated data retrieval and visualization.
Purpose:
This tool was developed to help financial analysts quickly assess the health of banks within specific geographic regions. It aggregated and incorporated visualizations of financial data, allowing analysts to quickly evaluate:
- Asset quality
- Earnings and profitability
- Liquidity risk
- Market sensitivity
A key feature of this tool was the ability to compare individual banks against industry benchmarks, such as median or aggregate financial metrics for peer institutions in the same market.
Technologies Used:
- Tableau – Developed 12 specialized dashboards, each focused on different financial risk factors.
- SAS (Statistical Analysis Software) – Pulled banking financial data, structured it for easy comparison, and performed statistical analyses to provide meaningful benchmarks.
Impact:
- Enabled faster and more accurate financial risk assessments.
- Provided visual comparisons of bank performance against industry standards.
- Improved decision-making by allowing users to identify early warning signs of financial instability.
