Internship Machine Learning Quant Jobs in Oxnard, CA

Position Overview
Apollo is seeking a Principal-level Structured Commercial Real Estate/Business-Purpose Resi loan Desk Strat to join its Global Investment Insights team in Los Angeles. This individual will be responsible for building and institutionalizing cash flow modeling, deal structuring analytics, and risk assessment capabilities across Apollo's structured CRE/BPL investment strategies, including Conduit CMBS, CRE CLO, Net Lease ABS, C-PACE, Residential Transitional Loans, Single Family Rental, Build-to-Rent, Landbanking, and Agricultural Loans.
This is a high-impact role at the intersection of quantitative analytics and structured commercial and business-purpose residential real estate investing, embedded within a centralized investment capability that serves the full breadth of Apollo's credit platform. The successful candidate will partner directly with investment teams, portfolio risk, and senior leadership to deliver scalable, code-based modeling frameworks that support pricing, structuring, and risk management for pools of commercial mortgage loans across multiple securitization formats.
The Role
As a Principal within Global Investment Insights, this individual will serve as the domain expert for structured CRE/BPL resi, owning the end-to-end quantitative framework for modeling commercial mortgage loan pools and their securitized structures. The role demands deep technical fluency in CRE/BPL collateral analysis, waterfall modeling, and tranche-level risk assessment, combined with the ability to operate as a strategic partner to investment professionals and build durable, enterprise-grade analytics. Consistent with Global Investment Insights' vision of embedding analytics and AI directly into investment workflows, the successful candidate will be expected to actively explore and integrate machine learning and AI techniques-such as automated collateral screening, property valuation models, and scenario generation-into the structured CRE/BPL analytical toolkit.
Primary Responsibilities
Cash Flow & Structure Modeling

• Design, build, and maintain cash flow models for pools of commercial mortgage loans across Conduit CMBS, CRE CLO, Net Lease ABS, C-PACE securitization formats, and for business-purpose residential loans across Residential Transitional Loans, Single Family Rental, Build-to-Rent, Landbanking strategies, and Agricultural loans.
• 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 both base-case and stress scenario analysis.
• Build and maintain collateral performance frameworks that enable systematic surveillance of underlying CRE loan pools across the portfolio lifecycle.

Investment & Structuring Support

• Partner with investment teams to provide quantitative analytics in support of new deal evaluation, pricing, and relative value assessment across structured CRE/business-purpose residential products.
• Develop scenario and sensitivity frameworks to assess the impact of macro variables (interest rates, cap rates, vacancy, rent growth) on deal economics and tranche-level returns.
• Support structuring decisions by modeling alternative capital structures, credit enhancement levels, and risk/return trade-offs for both primary issuance and secondary market opportunities.

Platform & Infrastructure

• Contribute to the development of Global Investment Insights' firmwide quantitative infrastructure by integrating structured CRE models into Apollo's centralized analytics platform, supporting real-time portfolio risk reporting and regulatory capital stress analytics.
• Identify and implement opportunities to apply machine learning and AI techniques to structured CRE/BPL workflows-including property valuation, collateral screening, anomaly detection in loan pool performance, and scenario generation-ensuring applied AI is grounded in the analytical infrastructure that supports how the firm invests.
• Benchmark and adopt leading modeling practices and technologies from peer institutions, ensuring Apollo's structured CRE/BPL capabilities remain best-in-class.
• Collaborate with technology and data teams to establish robust data pipelines, model governance, and version control practices for all structured CRE/BPL analytics.
• Provide mentorship and technical guidance to junior quantitative professionals supporting the structured CRE/BPL effort.

Qualifications & Experience

• Significant experience in structured credit, securitized products, or quantitative CRE 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 and/or Agricultural Finance.
• Demonstrated ability to build production-quality cash flow models for securitized CRE/business-purpose residential transactions, including loan-level collateral modeling and deal waterfall engines.
• Strong understanding of CRE and business-purpose residential fundamentals: 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 (e.g., Python, SQL, MATLAB, C# or equivalent).
• Familiarity with industry-standard structured finance cash flow modeling platforms and CRE/resi data providers is expected.
• Experience with securitization deal structures, credit enhancement mechanics, rating agency methodologies, and regulatory capital frameworks (Basel III / SCR) is strongly preferred.
• Excellent communication skills and the ability to translate complex quantitative concepts into actionable investment insights for senior stakeholders.
• Advanced degree in a quantitative discipline (finance, mathematics, statistics, engineering, computer science, or related field) preferred.
• Genuine conviction in the application of AI and machine learning to investment workflows. Experience applying ML techniques (e.g., gradient-boosted models, NLP for document extraction, neural networks for time series) to structured finance or real estate problems is a strong differentiator.
• A collaborative, "roll up your sleeves" mentality with a commitment to building scalable, institutional-grade analytics.

About Apollo
Apollo is a high-growth, global alternative asset manager. In our asset management business, we seek to provide our clients excess return at every point along the risk-reward spectrum from investment grade credit to private equity. For more than three decades, our investing expertise across our fully integrated platform has served the financial return needs of our clients and provided businesses with innovative capital solutions for growth. Through Athene, our retirement services business, we specialize in helping clients achieve financial security by providing a suite of retirement savings products and acting as a solutions provider to institutions. Our patient, creative, and knowledgeable approach to investing aligns our clients, businesses we invest in, our employees, and the communities we impact, to expand opportunity and achieve positive outcomes. As of December 31, 2025, Apollo had approximately $938 billion of assets under management. To learn more, please visit www.apollo.com.
Our Purpose & Core Values
Our clients rely on our investment acumen to help secure their future. We must never lose our focus and determination to be the best investors and most trusted partners on their behalf. We strive to be:

• The leading provider of retirement income solutions to institutions, companies, and individuals.
• The leading provider of capital solutions to companies. Our breadth and scale enable us to deliver capital for even the largest projects - and our small firm mindset ensures we will be a thoughtful and dedicated partner to these organizations. We are committed to helping them build stronger businesses.
• A leading contributor to addressing some of the biggest issues facing the world today - such as energy transition, accelerating the adoption of new technologies, and social impact - where innovative approaches to investing can make a positive difference.

We are building a unique firm of extraordinary colleagues who:

• Outperform expectations
• Challenge Convention
• Champion Opportunity
• Lead responsibly
• Drive collaboration

As One Apollo team, we believe that doing great work and having fun go hand in hand, and we are proud of what we can achieve together.
Our Benefits
Apollo relies on its people to keep it a leader in alternative investment management, and the firm's benefit programs are crafted to offer meaningful coverage for both you and your family.
Pay Range
$300,000
Apollo Global Management, Inc. (together with its subsidiaries and affiliates) is committed to championing opportunity.
The firm and its affiliates comply with applicable discrimination and equal opportunities legislation in all of its jurisdictions and do not discriminate in employment or recruitment based on race, color, religion, gender, national origin, veteran status, disability, age, citizenship, marital or domestic/civil partnership status, sexual orientation, gender identity or expression or any other protected characteristic under applicable law.
The contents of the qualifications and experience section of this job description are a guideline only. If an applicant can otherwise demonstrate their suitability for the role they will be considered.
The base salary range for this position is listed above. This position is also eligible for a discretionary annual bonus based on personal, team, and Firm performance. Compensation ranges are based on several factors including job function, level, and geographic location. Final offer amounts are determined by multiple factors including candidate experience and expertise, and may vary from the amounts listed here.