Security Modeling Associate

We are seeking a highly motivated Associate to join the Credit Modeling Team within AFE Single Security. This role is ideal for someone with a strong foundation in quantitative research, econometrics, and a passion for solving complex problems through innovation and collaboration. 

As part of our team, you will contribute to the development of next-generation financial models that directly support trading and portfolio management decisions. These models are built using cutting-edge techniques in data science, machine learning, and statistical modeling, and are deployed on scalable platforms using technologies. 

Model Research and Development: 

• Design, develop, and continuously enhance BlackRock’s Credit Risk Modeling Suite, covering private and public credit markets. This includes models for Probability of Default (PD), Loss Given Default (LGD), and Ratings Migration, calibrated to reflect the distinct characteristics of each market segment.  

• Integrate issuer-specific, deal-specific, and market-driven factors into model frameworks, capturing the nuances of corporate bonds, structured products, and private credit transactions such as direct lending and bespoke financing.  

• Stay at the forefront of academic research, regulatory developments, and industry best practices across investment-grade, high-yield, and private debt, translating insights into actionable model enhancements.  

• Contribute to the full lifecycle of credit risk models—from conceptualization and prototyping to validation, deployment, and ongoing performance monitoring—ensuring models remain robust, transparent, and fit-for-purpose.  

• Apply advanced statistical, econometric, and machine learning techniques to address challenges such as data sparsity, non-linear risk dynamics, and illiquidity premiums, especially prevalent in private markets.  

• Conduct rigorous model validation, benchmarking, and back-testing using diverse datasets, including market data, proprietary deal-level information, and external benchmarks.  

• Implement models in Python within the Aladdin platform, ensuring seamless integration with portfolio analytics, risk reporting, and investment decision tools.  

• Continuously enhance modeling infrastructure and workflows by leveraging automation, cloud-native technologies, and scalable data pipelines to improve efficiency and reproducibility.  

• Drive innovation by incorporating alternative data sources (e.g., ESG metrics, covenant compliance, private financials) and AI/ML techniques to improve predictive accuracy and expand model coverage.  

• Serve as a thought leader and subject matter expert, contributing to internal forums, client engagements, and cross-functional initiatives to promote model adoption and elevate credit analytics across the firm. 

Skills & Qualifications:  

• Demonstrated knowledge of credit modeling methodologies, such as structural models (e.g., Merton-type frameworks) and credit rating migration models. Experience with private credit modeling is considered beneficial. 

• Requires Master’s degree with 1-3 years, or bachelor’s degree with 3–5 years, of practical experience in developing and applying financial econometric models, emphasizing predictive analytics and quantitative risk frameworks.   

• PhD in quantitative fields such as Econometrics, Finance, Mathematics, Statistics, Computer Science, Data Science, or Financial Engineering in lieu of master’s degree with 2+ years also accepted. CFA or FRM certification preferred. 

• Advanced programming capabilities in Python, R, with practical experience in statistical computing, econometric analysis, and model deployment. 

• Strong conceptual grasp of financial market dynamics and the ability to contextualize quantitative insights within real-world macroeconomic and microstructural phenomena. 

• Exceptional verbal and written communication skills in English, with the ability to articulate complex quantitative concepts to both technical and non-technical stakeholders and external clients. 

• High degree of adaptability, intellectual curiosity, and professional maturity to thrive in a fast-paced, evolving environment. Proven ability to deliver high-quality output under tight deadlines.