Staff Analyst, Investor Analytics

Role overview

Own the credit and performance narrative for a home-equity lending portfolio and provide the analysis, reporting, and infrastructure that institutional capital partners use to evaluate risk. The role combines portfolio analytics, financial modeling, recurring reporting, investor communication, and cross-functional leadership. You will translate complex performance data into clear conclusions about current results, forward risk, and deal strategy.

Responsibilities

- Partner directly with capital markets and lending teams to explain platform performance, build investor confidence, and shape capital solutions. - Analyze delinquency, arrears, roll rates, vintage and cohort loss curves, model calibration, feature importance, yield, defaults, and prepayments. - Serve as a trusted point of view on portfolio performance and communicate drivers, risks, and implications to investors and internal leadership. - Produce recurring performance reports and forecasts that support capital partners, management decisions, and transaction strategy. - Build financial models, data pipelines, automated monitoring, and reporting infrastructure that make credit insights timely and reliable. - Collaborate with machine learning, product, engineering, data, and finance teams to define metrics and align on product performance. - Mentor colleagues and help raise the quality and consistency of analytical work.

Requirements

- At least five years of professional experience in financial services, with a focus on credit, debt, consumer or structured credit, private credit, securitization, or credit capital markets. - Hands-on experience analyzing and explaining loan portfolio performance and credit risk. - Strong Python and SQL skills, including work with large datasets, data modeling, and robust analytical pipelines. - Familiarity with platforms and tools such as Databricks, Redshift, dbt, and business intelligence systems. - Degree in finance, economics, statistics, engineering, data science, or another quantitative discipline. - Demonstrated ability to collaborate with finance, product, data engineering, and machine learning teams. - Excellent executive communication and storytelling skills, with the ability to make technical analysis useful to varied audiences.

Nice to have

- Experience with home-equity lending, securitization, capital raising, or institutional investor relationships. - Experience using AI-assisted or agentic development tools to automate analytical pipelines, monitoring, and reporting.

Benefits and work setup

The role is remote with periodic in-person collaboration and possible travel. The source describes location-dependent compensation and benefits that may include performance incentives, equity, retirement contributions, health coverage, paid leave, wellness and productivity support, and employee community programs.