SVP, Product Manager

Pennymac • Westlake Village, CA

4h • Onsite

About The Position

The SVP, Product Manager is a high-impact individual contributor role at Pennymac, a specialty financial services firm focused on U.S. mortgage loans. This role requires expertise in both quantitative finance and applied machine learning. The Senior AI Product Manager will manage the entire product lifecycle for capital markets AI initiatives, from discovery and roadmap definition to technical delivery and benefits realization. The position involves deep engagement with trading desks, risk management, portfolio management, and capital markets operations. The ideal candidate must be capable of operating strategically with capital allocators and possess the technical depth of a machine learning engineer or data scientist, translating complex desk workflows into production-grade AI solutions that enhance efficiency, risk posture, and revenue capture.

Requirements

• Advanced degree in a quantitative discipline: MS in Data Science, Machine Learning, Statistics, Financial Engineering, or Computer Science from an accredited program.
• CFA charter holder or MBA from a recognized business school — the combination of rigorous quantitative training with structured financial or strategic thinking is central to this role’s remit.
• 6+ years of combined experience in AI/ML product development and financial services — with demonstrated ability to operate across both domains, not merely adjacent to them.
• Prior background in financial services in one or more of the following: pricing analyst, quantitative PM at a mortgage fintech, MBS trader, capital markets risk analyst, or financial data scientist.
• Proven track record shipping enterprise AI solutions with measurable business impact in complex, regulated organizations at scale.
• Hands-on coding proficiency (Python preferred) sufficient to collaborate with engineering on experimental-to-production transitions, evaluate model outputs, and construct evaluation harnesses — not merely read dashboards.
• Deep understanding of LLM architectures, prompting strategies, RAG pipelines, context engineering, fine-tuning, MCP, and agentic frameworks.
• Experience with MLOps platforms, AI governance frameworks, and the full AI/ML lifecycle: development, deployment, monitoring, and enterprise integration.
• Ability to define evaluation sets, lead quantitative and qualitative iteration cycles, and distinguish signal from noise in model performance data.
• Strong mortgage industry knowledge: securitization mechanics, RMBS structure, capital markets workflow architecture, MSR valuation, hedging operations, and pull-through modeling.
• Familiarity with financial risk frameworks, model risk governance, and regulatory compliance considerations applicable to AI deployment in financial services.
• Strong PM foundation: ability to translate complex, ambiguous business needs into precise technical specifications, manage stakeholder ambiguity, and make defensible prioritization decisions under pressure.

Nice To Haves

• Preference given to candidates who hold both a quantitative MS and either a CFA or an MBA, reflecting fluency across the technical and capital markets dimensions of the role.

Responsibilities

• Drive end-to-end AI product lifecycle across all capital markets workstreams—from discovery and requirements definition through development, testing, launch, and post-launch optimization.
• Manage a unified AI backlog spanning the full CM value chain; govern cross-pod dependencies, sequencing, and resource allocation with disciplined prioritization.
• Translate complex desk workflows and business problems into clear Product Requirement Documents, user stories, functional acceptance criteria, and success metrics.
• Drive build-versus-buy evaluations and manage vendor assessments for optimal delivery outcomes, including third-party AI platforms and LLM API integrations.
• Conduct structured market research and competitive intelligence to surface high-impact AI use cases across secondary markets, MSR operations, hedging, and pull-through forecasting.
• Embed with LOB stakeholders—desk heads, operations managers, and risk leads—to surface latent requirements and validate opportunity sizing before committing roadmap capacity.
• Integrate discovery findings into a sequenced, risk-adjusted roadmap aligned to organizational priorities, FHFA compliance posture, and available engineering capacity.
• Partner cross-functionally with engineering pods, data science, and the AI Accelerator team to ship automations and copilots aligned to desk workflows—daily hedge + P&L explain, exceptions triage, pull-through reforecast, and MSR valuation workflow assist.
• Drive experiment design standards, A/B testing frameworks, evaluation set construction, and benefit attribution methodology across all AI pods.
• Coordinate release trains and vendor integrations for shared infrastructure (LLM APIs, vector stores, evaluation harnesses, and MLOps tooling).
• Partner with compliance, legal, and data governance to ensure all AI solutions satisfy SR 11-7 model risk governance, explainability, and regulatory standards.
• Track and report benefits realization—hedge P&L improvement, pull-through accuracy, funding cost reduction, MSR mark accuracy—to leadership on a quarterly basis.
• Lead adoption telemetry, user training programs, and iterative improvement cycles post-launch; own the relationship between shipped products and demonstrated desk behavior change.
• Stay current on frontier AI techniques and industry trends; act as the internal subject matter authority on AI product development best practices.

Benefits

• Comprehensive Medical, Dental, and Vision
• Paid Time Off Programs including vacation, holidays, illness, and parental leave
• Wellness Programs, Employee Recognition Programs, and onsite gyms and cafe style dining (select locations)
• Retirement benefits, life insurance, 401k match, and tuition reimbursement
• Philanthropy Programs including matching gifts, volunteer grants, charitable grants and corporate sponsorships
• Competitive salary
• Bonus opportunities
• Stock-based incentives

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Number of Employees: 501-1,000 employees