Portfolio Management

Who We Are

Cross River builds the infrastructure behind the world’s most innovative financial products. Our technology and capital solutions power payments, cards, lending, and digital asset capabilities that move money safely, instantly, and inclusively — trusted by leading fintechs, enterprises, and disruptors across the globe.

Our mission is simple: to build the financial infrastructure that expands access and opportunity for all. Guided by a culture of collaboration, curiosity, and purpose, Cross River has been named one of American Banker’s Best Places to Work in Fintech year after year. Whether you’re designing code, solving regulatory puzzles, or developing strategy, you’ll join a team where innovation and integrity drive everything we do — and where your work helps shape the future of finance.

What We're Looking For

The Quantitative Strategies Group (QSG) at Cross River is seeking a Vice President, Portfolio Management to join its growing team. The team sits within the Capital Solutions Group (CSG) and serves as a centralized function for investment intelligence and quantitative decision making across investment, structuring, and portfolio management initiatives.

We are seeking a quantitatively driven Portfolio Management professional to join our group. This role sits at the intersection of credit analytics, financial modeling, and portfolio surveillance - ensuring that our positions are rigorously tracked, appropriately reserved, and performing in line with original underwriting expectations. The ideal candidate brings hands-on experience with cash flow modeling, ABS structures, and a strong technical toolkit to support data-driven portfolio insights. The individual will also serve as a senior resource within the group, mentoring junior team members, instilling best practices around modeling/surveillance/structured credit analysis, and helping codify institutional knowledge into repeatable, scalable processes.

Responsibilities:

Credit Evaluation

• Develop and maintain analytical and statistical frameworks to evaluate collateral pools, form views on key pricing assumptions (e.g., prepayment speeds, default/loss curves). Maintain and update assumption sets based on realized performance
• Work hands-on with large loan-level datasets using Python and SQL to build analytical frameworks that evaluate collateral performance, identify risk concentrations, and inform assumption-setting across the portfolio
• Build and maintain detailed cash flow models to project expected returns, losses, and structural outcomes under base, upside, and stress scenarios
• Evaluate deal structures, waterfall mechanics, triggers, credit enhancement levels, and subordination to assess current and projected credit risk