- Prepare and normalize raw collateral and deal data into analyzable fields, performing quality checks and flagging anomalies or inconsistencies (including developing a strong understanding of data definitions, reporting conventions, and how collateral characteristics impact performance and valuation across multiple asset classes)
- Perform pool, portfolio, and transaction analytics using internal models and agreed-upon assumptions, working with trading, structuring, sales, banking and other partners on custom scenarios and sensitivities (framing key drivers and trade-offs, identifying assumption sensitivities, and articulating implications for pricing, risk, and execution)
- Support financing and securitization analysis by assessing structural considerations at a high level, including concepts such as credit enhancement and loss coverage, advance rates and haircuts, and key term comparisons across market conventions
- Maintain and use internal databases and trackers of securitizations and transactions to compare structures, bond sizing, and deal terms across sectors and asset classes
- Run ad hoc pricing, scenario, and cashflow analysis in industry analytics platforms (e.g., Intex, Bloomberg, OASis) and proprietary Python-based models
- Produce clear written materials and summaries for stakeholders, highlighting risks, sensitivities, data limitations, and execution considerations; be prepared to discuss findings with internal and external partners as needed
Required Qualifications
- Bachelor’s degree (or equivalent practical experience) in computer science, engineering, economics, or finance
- Strong analytical, problem solving, and quantitative skills
- Excellent communication skills and strict attention to detail, including the ability to identify patterns and anomalies in data, explain findings clearly, and work effectively with multiple stakeholders
- Understanding of fixed income mathematics and cash flows
- Comfort working under time pressure, prioritizing across concurrent requests, and managing timelines and deliverables in a fast-paced environment
Preferred Qualifications (Bonus)
- Experience or demonstrated interest in structured products and securitized markets across a broad set of asset classes (e.g., ABS, MBS, CMBS, CLO, consumer, and other securitized collateral types)
- Experience with Python or other scripting languages, and familiarity with databases and data pipelines
- Experience with industry analytics tools (e.g., Intex) and/or internal pricing and modeling frameworks
- Familiarity with automation and AI-assisted tools as a productivity aid in research or analysis
Skills and Competencies
Successful Analysts on the team are disciplined, detail-oriented, and rigorous in how they validate inputs and assumptions. They can structure ambiguous questions into actionable analyses, communicate clearly in writing and verbally, and produce decisioning materials that distinguish facts, assumptions, analysis, and conclusions. They collaborate effectively across product specialists and stakeholders, incorporate feedback quickly, and maintain strong ownership of deliverables from initial request through final output, with an emphasis on execution quality, judgment, and timeliness.