Associate Director [Multiple Positions Available]

KBRA•New York, NY

9h•$153,000 - $160,000•Hybrid

About The Position

This role involves executing valuation and credit methodologies using quantitative and statistical modeling to assess expected losses and determine valuations/credit ratings. The Associate Director will periodically operate valuation/credit models to ensure compliance with methodologies and guidelines, and review financial credit models for adherence to rating methodologies and commercial real estate evaluation principles. The position also requires acting as the team's data expert, maintaining the CMBS database, developing a system for uploading credit modeling data, and troubleshooting data-related issues with the IT team. Responsibilities include conducting detailed cash flow analysis and valuations, occasionally leading new issuance and surveillance transactions, and managing deals. The role also involves writing and publishing research papers on credit trends and market outlooks, participating in the creation and improvement of financial credit models, and directing and training junior analysts and associates on daily working guidelines and credit models.

Requirements

Bachelor’s degree in financial engineering, operations research, accounting, mathematics, or real estate finance, plus five years of experience in commercial mortgage-backed securities, or structured finance, or investment banking, or finance and accounting, or other commercial real estate finance experience and interest.
Master’s degree in financial engineering, operations research, accounting, mathematics, or real estate finance, plus two years of experience in commercial mortgage-backed securities, or structured finance, or investment banking, or finance and accounting, or other commercial real estate finance experience and interest.
2 years of experience applying advanced principles of finance, accounting, mathematical and/or statistical analysis.
2 years of experience performing advanced/expert Microsoft Excel functions (including mastery over formulas and shortcuts) to analyze large amounts of data to conduct day-to-day responsibilities in prior roles.
1 year of experience in data engineering or data science.
1 year of experience in working with different types of valuation and/or credit models, or financial statement analysis.
Expertise in U.S. commercial real estate sectors and capital markets as demonstrated by 1 year of experience and/or coursework amounting to a specialization in Real Estate.
1 year of experience in developing and maintaining the relational database (RDBMS), writing SQL queries and Excel VBA codes.
Must successfully complete competency-based interview.

Responsibilities

Execute valuation and credit methodologies by operating valuation/credit models; use quantitative and statistical modelling to assess expected losses to determine valuations/credit ratings.
Operate valuation/credit models on a periodic basis; to assess if outstanding valuations/credit ratings are still in compliance and adhering to methodologies and evaluation guidelines.
Review varied financial Credit models and ensure it is executed in accordance with rating methodologies and in compliance with commercial real estate evaluation guidelines and principles.
Act as the data expert for the team and maintain the CMBS database; develop a system to upload credit modeling data to the database; troubleshoot and co-operated with IT team if any data-related issue arises.
Conduct detail cash flows analysis and valuation; occasionally lead end-to-end new issuance and surveillance transactions along with overall deal management in accordance with organizational guidelines for various transaction types.
Write and publish topical research papers and commentary on credit trends, real estate market outlooks, and industry-specific relevant topics.
Participate in creating and improving existing financial credit models; property cash flow and underwriting templates.
Direct and lead junior analysts and associates on the daily working guidelines of the Analytics team, including train new hires on credit models.