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Apollo Global

Invests client and insurance money in private credit

Principal – Structured Commercial Real Estate/BPL Resi Desk Strat

Quantitative RiskConfirmed live in the last 24 hours
Full-timeWoodland Hills, Los Angeles, CA, USA

About the Job

Requirements

  • Significant experience in structured credit, securitized products, or quantitative commercial real estate or business-purpose residential analytics, with deep domain expertise across one or more of Conduit CMBS, CRE CLO, Net Lease ABS, C-PACE, SFR/BTR, Residential Transitional Loans, Landbanking, or Agricultural Finance.
  • Demonstrated ability to build production-quality cash flow models for securitized commercial real estate or business-purpose residential transactions, including loan-level collateral modeling and deal waterfall engines.
  • Strong understanding of commercial real estate and business-purpose residential fundamentals, including property-level underwriting, capitalization rates, net operating income, debt service coverage, and loan-to-value dynamics.
  • Proficiency in programming languages and quantitative tools commonly used in structured finance modeling, such as Python, SQL, MATLAB, C#, or equivalent.
  • Familiarity with industry-standard structured finance cash flow modeling platforms and commercial real estate/residential data providers.
  • Ability to translate complex quantitative concepts into actionable investment insights for senior stakeholders.
  • Conviction in applying artificial intelligence and machine learning to investment workflows.
  • Collaborative, hands-on approach and commitment to building scalable, institutional-grade analytics.

Responsibilities

  • Design, build, and maintain cash flow models for pools of commercial mortgage loans across Conduit CMBS, CRE CLO, Net Lease ABS, and C-PACE securitization formats, and for business-purpose residential loans across Residential Transitional Loans, Single Family Rental, Build-to-Rent, Landbanking, and Agricultural loan strategies.
  • Develop standardized, code-based waterfall engines that model deal structures, including credit enhancement, sequential and pro-rata pay tranches, reserve accounts, interest rate hedging, and loss allocation mechanics.
  • Construct loan-level default, loss severity, and prepayment models calibrated to property type, geography, leverage, and borrower characteristics, supporting base-case and stress scenario analysis.
  • Build and maintain collateral performance frameworks for systematic surveillance of underlying commercial real estate loan pools across the portfolio lifecycle.
  • Partner with investment teams to provide quantitative analytics supporting new deal evaluation, pricing, and relative value assessment across structured commercial real estate and business-purpose residential products.
  • Develop scenario and sensitivity frameworks to assess how macro variables, including interest rates, capitalization rates, vacancy, and rent growth, affect deal economics and tranche-level returns.
  • Support structuring decisions by modeling alternative capital structures, credit enhancement levels, and risk/return trade-offs for primary issuance and secondary market opportunities.
  • Integrate structured commercial real estate models into the centralized analytics platform to support real-time portfolio risk reporting and regulatory capital stress analytics.
  • Identify and implement applications of machine learning and artificial intelligence in structured commercial real estate and business-purpose residential workflows, including property valuation, collateral screening, anomaly detection in loan pool performance, and scenario generation, grounded in the firm's investment analytics infrastructure.
  • Benchmark and adopt modeling practices and technologies from peer institutions.
  • Collaborate with technology and data teams to establish robust data pipelines, model governance, and version control practices for structured commercial real estate and business-purpose residential analytics.
  • Provide mentorship and technical guidance to junior quantitative professionals supporting the structured commercial real estate and business-purpose residential effort.

Desired Qualifications

  • Experience with securitization deal structures, credit enhancement mechanics, rating agency methodologies, and regulatory capital frameworks such as Basel III or SCR.
  • Experience applying machine learning techniques, such as gradient-boosted models, natural language processing for document extraction, or neural networks for time series, to structured finance or real estate problems.

About the Company

Apollo Global

Invests client and insurance money in private credit

Apollo Global Management invests money for pension funds, insurers, wealthy individuals and its own retirement business, with most of its assets in private credit, meaning loans arranged directly with companies rather than bought on public markets. It also runs private equity and real estate funds, and its buyout teams have a long record of backing troubled or complex companies. Apollo owns Athene, a retirement insurer that sells annuities and gives the premiums to Apollo to invest, so the firm earns fees from clients plus the spread between Athene's investment returns and what it pays policyholders. Apollo was founded in 1990 and is based in New York.

Company size
5,001-10,000
Company stage
IPO
Headquarters
New York City, New York
Founded
1990

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