Private Asset Market Risk Modeler, Vice President

About this role Join a diverse and collaborative team of over 400 modelers and technologists in Aladdin Financial Engineering (AFE) within BlackRock Solutions, the business responsible for the research and development of Aladdin’s financial models. This group is also accountable for analytics production, enhancing the infrastructure platform, and delivering analytics content to portfolio and risk management professionals (both within BlackRock and across the Aladdin client community). The models developed and supported by AFE span a wide array of financial products covering equities, fixed income, commodities, derivatives, and private markets. AFE provides investment insights that range from an analysis of cash flows on a single bond, to the overall financial risk associated with an entire portfolio, balance sheet, or enterprise. We are looking to hire a senior quant modeler ( VP ) to join our Private Asset Market Risk Modeling team to drive the development of risk factor models for private market investments . The Private Asset Market Risk team builds a range of models, including private equity, real estate, credit, infrastructure, and hedge funds , with sophisticated econometric/statistical methods and tools. The se models have real practical value and have a very large footprint of usage across the entire Aladdin client base including portfolio managers, risk managers, and allocators and influence investment activity. As a result, w e place special emphasis on developing models that scale with our growing Analytics’ business and ensuring adherence to BlackRock’s rigorous standards of model governance. This individual would have a strong background in quantitative research, have demonstrable project management skills as well as proven experience to work in a team environment as well as collaborating with senior modelers from other groups/regions. This person is expected to join as an individual contributing to the design and development of our private market risk models, particularly in the private credit (i.e., real estate debt, infrastructure debt) space. About the role Develop private credit risk factor models and  back test , document, and guide new models and methodologies through validation . Collaborate with partner teams on model productioniz ation Build and maintain model governance controls, including (but not limited to) model performance monitoring, model documentation, model remediations and supporting internal & external client model validations Communicate (verbally and in writing) with internal stakeholders and external clients on the design, backtesting , and usage of the models. Discuss model performance regularly, investigate exceptional model performance, diagnose issues and conduct corrective remediations About you Extensive experience in quantitative field / statistical modeling . Experience with one or more of the following is preferred: risk factor models and analytics, domain knowledge of fixed income securities , applications of ML/AI techniques . Master’s or PhD degree in a quantitative discipline or one that relates to application of quantitative techniques in finance (f inancial engineering, math f inance, etc. ) . Master ’s degree with 5 years or PhD degree with 3 years of experience. A strong background in data-driven quantitative research , econometrics, and empirical asset pricing Hands-on experience with statistical modeling through software (e.g., Python, R) and strong background in programming . Proficiency with Python is required Experience with data handling (ETL, data joining with SQL, cleaning, processing, summarizing, descriptive analysis), and building and back-testing statistical and econometric models Knowledge of investments, portfolio management is preferred Experience with any version control system (e.g., git) is strongly preferred Prior work experience in financial modeling (e.g., risk models, ... (truncated, view full listing at source)