Program Associate, Investment Analytics

Global Atlantic Financial Group•New York, NY

1d•$160,000•Onsite

About The Position

Global Atlantic Financial Company (a subsidiary of Global Atlantic Financial Group Limited) is seeking a candidate for the position of Program Associate, Investment Analytics in New York, NY. Responsibilities include: Build and test cashflow projections and pricing models incorporating Moody’s Commercial Mortgage Metrics (CMM) and desk assumptions for Commercial Mortgage-Backed Securities and Commercial Mortgage Loans. Leverage Moody’s CMM to calculate Expected Losses for Commercial Mortgage Loans (CML) and Commercial Mortgage-Backed Securities (CMBS) and identify key risk drivers. Conduct research on Single Asset Single Borrower (SASB) CMBS historical payoffs, extension options/executions, and defaults using Intex data to spot market trends and better assess the existing portfolio’s risk and performance. Calculate scenario yield and weighted average life sensitivities as part of impact analysis of prepayment and extended payoff assumptions. Analyze CML historical performance by calculating combined yields using remittances and future cashflows. Implement and maintain investment-oriented applications on Beacon to improve the efficiency of investment management and build interactive dashboards on Tableau. Run and monitor daily, weekly, and monthly processes to ensure the portfolio’s data accuracy and quality. Work with senior team members to address various requests from portfolio management teams and other internal stakeholders.

Requirements

Master’s degree in Quantitative Finance, Financial Engineering, Statistics, or similar quantitative fields of study, plus two (2) years of experience as a quantitative analyst or related role.
OR
Bachelor’s degree in Quantitative Finance, Financial Engineering, Statistics, or similar quantitative fields of study, plus four (4) years of experience as a quantitative analyst or related role.
One (1) year of experience in the following:
Working in fixed income markets and instruments, including quantitative analytics of commercial mortgage-backed securities and commercial mortgage loans.
Working with Python and using Python data analysis packages, such as pandas, numpy, or scipy.
Applying understanding of databases to handle complex queries to large data tables using Amazon Redshift SQL.
Building and maintaining business intelligence dashboards in Tableau using SQL queries.
Working with Excel and Pivot tables to calculate complex financial cashflows and yields.
Using Intex data to analyze the performance and sensitivities of commercial mortgage-backed securities.
Building and maintaining investment-oriented applications on the Beacon platform.
Running performance forecasts using Moody’s Commercial Mortgage Metrics (CMM) software to assess default and recovery for commercial real estate mortgages.

Responsibilities

Build and test cashflow projections and pricing models incorporating Moody’s Commercial Mortgage Metrics (CMM) and desk assumptions for Commercial Mortgage-Backed Securities and Commercial Mortgage Loans.
Leverage Moody’s CMM to calculate Expected Losses for Commercial Mortgage Loans (CML) and Commercial Mortgage-Backed Securities (CMBS) and identify key risk drivers.
Conduct research on Single Asset Single Borrower (SASB) CMBS historical payoffs, extension options/executions, and defaults using Intex data to spot market trends and better assess the existing portfolio’s risk and performance.
Calculate scenario yield and weighted average life sensitivities as part of impact analysis of prepayment and extended payoff assumptions.
Analyze CML historical performance by calculating combined yields using remittances and future cashflows.
Implement and maintain investment-oriented applications on Beacon to improve the efficiency of investment management and build interactive dashboards on Tableau.
Run and monitor daily, weekly, and monthly processes to ensure the portfolio’s data accuracy and quality.
Work with senior team members to address various requests from portfolio management teams and other internal stakeholders.

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