Job Description
About TeamSec:
TeamSec offers Securitization-as-a-Service, blending AI-driven analytics and structured finance expertise. Our platform empowers clients to convert assets into securities, enhancing liquidity access and market growth.
Position Overview:
We are seeking a seasoned Quantitative Analyst with 5+ years in securitization, with specific experience in Asset-Backed Securities (ABS) and Mortgage-Backed Securities (MBS). This role involves advanced data analysis, model development, and supporting valuation and pricing functions. Candidates must demonstrate expertise in financial engineering, securitization modeling, and risk analysis.
Key Responsibilities:
* Model Development : Design and test sophisticated valuation, pricing, and risk assessment models for ABS and MBS products.
* Valuation and Pricing : Execute in-depth securitization asset valuation and pricing analyses, factoring in market dynamics, cash flows, and collateral analysis.
* Risk & Scenario Analysis : Perform comprehensive sensitivity, scenario, and stress testing on ABS and MBS assets, identifying and mitigating risks.
* Algorithm Development : Develop and optimize models for prepayment, default, and yield curve analyses, including scenario analysis for ABS and MBS.
* Portfolio Support : Collaborate with portfolio managers to fine-tune securitization portfolios, ensuring adherence to risk thresholds.
* Client Reporting : Deliver quantitative findings to stakeholders, articulating model outputs and insights on securitized asset performance.
Qualifications:
* Experience : Minimum of 5 years in securitization or structured finance, with substantial experience in valuation and pricing.
* Technical Skills : Advanced proficiency in Python, R, SQL, and financial modeling tools; VBA and Excel are also highly valued.
* Financial Knowledge : Robust knowledge of ABS/MBS structures, yield curve modeling, and structured finance fundamentals.
* Analytical Skills : Demonstrated capacity for handling complex datasets and conducting detailed risk assessments.
* Desired Skills : Experience in data analytics with tools like Pandas, Numpy, and SciPy, and familiarity with ARIMA and GARCH forecasting methods, as well as S&P credit performance methodologies, are highly desirable.