Portfolio Modeling, Private Credit VP/SVP

The VP/SVP - Portfolio Modeling, Private Credit position is responsible for developing, improving, and managing detailed fund models that capture historical and projected performance, ensure compliance with leverage restrictions, and calculate investment and fund-level metrics for the Private Credit business. Working closely with portfolio management, risk management, investor relations, and accounting teams, this role facilitates investment decision-making and operational processes. They create and maintain fund-level models for analytics, monitoring, forecasting, and ad-hoc support for distressed, opportunistic, and private credit funds. In summary, the VP/SVP - Portfolio Modeling, Private Credit is a vital member of the Portfolio Analytics team, providing valuable insights and support for multiple closed-end funds in the Private Credit business.

JOB RESPONSIBILITIES

Develop and maintain robust and scalable fund models for private credit funds.

Create and maintain fund-specific dashboards summarizing portfolio positioning, performance, and projections.

Produce performance and attribution reports for multi-asset class portfolios.

Establish and implement processes for generating timely and accurate performance reports.

Collaborate on automation, efficiency improvement, and thought leadership initiatives.

Review asset valuations and communicate performance impacts to the portfolio management team.

Coordinate with cross-functional teams to facilitate fund operation, management, and reporting

Skills and Experience:

5-10+ years of experience in Private Credit portfolio/fund modeling.

Strong background in Fixed Income, Real Estate, and Private Credit, including derivatives.

Ability to create detailed and dynamic forecast models, summarize results, and effectively communicate to senior leadership and external clients.

Advanced Excel skills for creating advanced forecasting and waterfall models with minimal supervision.

Familiarity with SQL, Python, .Net, and iLevel.

Bachelor's degree in a quantitative discipline, advanced degree preferred.

Strong communication skills and ability to work well under pressure with multiple tasks.

Willingness to work extended hours as needed.