Professional Experience

Led ESG Analysis of Resi Whole Loan Portfolio

• Climate Risk

  Analyzed climate risk for 60,000+, $16 billion portfolio of residential whole loans in the United States from floods, heat stress, hurricanes & typhoons, sea-level rise, and water stress using third-party risk tool and Python for geospatial analysis

  
  

  Advised senior leaders of these findings and recommended a preliminary climate risk mitigation strategy

• Community Reinvestment Act (CRA)

  Analyzed portfolio allocations to CRA-eligible census tracts using Python, SQL Server, and the Census Bureau geocoder, based on legal research into the Code of Federal Regulations and applicable federal agency guidance

  
  

  Advised senior leaders of our sizeable CRA exposure for our $16 billion portfolio, which enhances our ESG profile due to indirect lending to distressed, underserved, or low- and moderate-income census tracts

Created Due Diligence Tool

Utilized Python to create a tool to compare due diligence modification reports from third-party providers with seller data for loan pools, saving time and streamlining previously manual processes to review 30+ data fields

Created Dynamic CECL Dashboard in Power BI

Enhanced team’s understanding of current expected credit loss (CECL) reserves across time for the $16 billion resi whole loan portfolio in conjunction with US national unemployment data and portfolio book yield by creating a dynamic dashboard in Power BI processing 5 million+ rows of historical data from SQL Server

Iteratively optimized SQL queries supporting the dashboard to cut loading time from 30+ minutes to under 10 minutes

LIBOR to SOFR Transition Project

Led fellow interns to analyze the pace of transition from LIBOR to SOFR in the futures, swaps, and new bond issuance markets using Bloomberg data

Presented takeaways to members of the MIM derivatives team using a professionally formatted slide deck with MIM colors / branding

Enhanced Research Data Analytics through Implementation of Advanced Technology Tools

Led a team of 5 analysts, associates, and associate directors in designing and architecting a more efficient analytics and visualization platform for MetLife Investment Management’s Risk, Research & Analytics team using Power BI and the cloud.

This implementation streamlined previously manual research and analytical processes, increasing efficiency, accuracy, and actionable insights from several of MetLife’s key Real Estate Research processes.

Evaluated, Selected, and Implemented a Climate Risk Assessment Process

Evaluated seven climate change forecasting firms’ capabilities in partnership with MIM Real Estate’s in-house architects and event risk management teams.

Developed a bespoke methodology for evaluating climate change risk in commercial real estate debt and equity deals, allowing for early up-front detection and ongoing analysis of the financial risks associated with longer-term climate change on real estate investment opportunities. All new assets sourced for the MIM platform must incorporate this risk assessment, which directly impacts deal approval.

Augmented Retail Real Estate Information to Enhance Portfolio Management Effectiveness in the COVID-19 Environment

• Co-Tenancy Project

  Built a co-tenancy tracker in Power BI for MIM’s $6+ billion retail loan portfolio to proactively identify pockets of existing or emerging potential stress within individual retail loans based on underlying co-tenancy lease clauses.

  
  

  This tool allows management to quickly and more accurately assess portfolio risks related to specific retailer names throughout the evolution of the COVID-19 pandemic and engage borrowers in early discussions.

• Retail Risk Report

  Co-created a dynamic Power BI report to track the impact of bankruptcies and store closures on MIM’s debt and equity portfolios of $8+ billion in retail assets.

  
  

  This tool streamlined retail risk reporting, enabling portfolio managers to quantify the impact of bankruptcies and store closures on asset- and loan-level performance.

Enriched Nationwide Asset-Level Data for Enhancing Real Estate Insurance Management Platform

Coordinated with 40 asset managers and architects across MRE’s regional offices to source data and documentation for a significant overhaul of MIM’s insurance and risk platform, leading to more precise insurance cost management and forecasting in business plan development and property performance projections.

Analyzed Restaurant Portfolio Exposure and Industry Outlook

At the start of the pandemic, examined restaurant equity portfolio exposure to major restaurant categories. The analysis revealed that fast-casual restaurants comprise 30% of MRE’s restaurant equity portfolio square footage. This sector is expected to outperform during the pandemic given its affordable cost and delivery and take-out capabilities.

Presented analysis to Risk, Research & Analytics team, and mitigated senior management’s concerns about restaurant exposure risk.

Drafted Comprehensive RMBS Manual for New Hire Training and Reference Purposes

Coordinated across four groups of interns to draft sections of a comprehensive 80+ page, 20,000+ word manual outlining concepts of RMBS, residential whole loans, mortgage servicing, and GSEs.

This new manual will facilitate faster new hire onboarding and create a centralized point of reference for the broader team.

Valuations & Ratings Support

Reviewed debt and equity valuations for office and multifamily assets based on third-party appraisal reports. Verified third-party and regional analyst assumptions and ARGUS models to ensure accurate valuations.

Using third-party data sources and internal documents, conducted multifamily commercial mortgage ratings on two assets with combined $133 million PBO in the Southeast Region. The analysis provided updated information to clients on the assets’ risk levels stemming from COVID-19, such as impacts to leasing and rent metrics, within their respective portfolios.

Recommended a Public Fixed Income Investment Based on Credit Research

Produced a report with an investment recommendation based on CSX Corp’s creditworthiness and presented it to members of the Global Credit Research team.

Utilized Moody’s credit research, Bloomberg Terminal, CSX Corp public documents, and other sources to qualitatively and quantitatively determine the company’s creditworthiness.