About this roleAFE is a diverse and global team with a keen interest and expertise in all things related to technology and financial analytics. The group is responsible for the research and development of quantitative financial and behavioral models and tools across many different areas - single-security pricing, prepayment models, risk, return attribution, liquidity, optimization and portfolio construction, scenario analysis and simulations, covering all asset classes. The group is also responsible for the technology platform that delivers those models to our internal partners and external clients, and their integration with Aladdin.
AFE conducts leading research on the areas above, delivering state-of-the-art models. AFE publishes applied scientific research frequently, and our members present regularly at leading industry conferences. AFE engages constantly with the sales team in client visits and meetings.
Role We are seeking a hands-on Quantitative Associate to join the Portfolio Risk team within AFE. This role is ideal for someone who enjoys working deeply with data and code, has strong attention to detail, and is motivated to build practical, production-ready risk models and analytics used by real investment professionals.
This is an individual contributor role focused on quantitative research, model development, testing, and implementation. Formal project management responsibilities are not required, but the role does require strong ownership of work, critical thinking, and the ability to collaborate effectively with researchers, engineers, and stakeholders across regions.
The Portfolio Risk team develops and maintains a broad set of analytics, including:
- Multi-factor Linear risk models
- Value-at-Risk (VaR) methodologies
- Volatility and covariance matrix estimation
- Portfolio stress testing and scenario analysis
These models are widely used across Aladdin and directly influence investment and risk management decisions. As a result, the team places strong emphasis on
model rigor, governance, scalability, and transparency.
This role also offers the opportunity to contribute directly to the team's AI transformation journey, particularly in applying AI and automation to modernize and scale model governance workflows.
What You Will Do- Research, design, and back-test portfolio risk models using Python-based infrastructure
- Work hands-on with large and complex financial datasets, ensuring data quality and robustness of results
- Collaborate closely with software engineers to test, productionize, and maintain models
- Support existing models in production, including investigation and resolution of model-related questions from internal stakeholders and clients
- Develop and enhance testing, validation, back-testing, and quality-control frameworks
- Contribute to the team's AI transformation journey, with a focus on applying AI, ML, and automation to model governance processes, such as:
- Model validation and back-testing
- Testing and quality control
- Documentation and reproducibility checks
- Research-to-production code migration
- Clearly document and communicate model assumptions, results, and limitations to both technical and non-technical audiences
Skills & Qualifications: - Master's degree (e.g., MFE) or PhD in a quantitative field such as Finance, Economics, Mathematics, Statistics, Computer Science, or Engineering
- Strong hands-on programming experience, primarily in Python (R a plus)
- Experience working with large datasets and applying statistical, econometric, or quantitative techniques
- Solid understanding of financial markets, financial products, and basic economics
- Strong analytical and problem-solving skills with high attention to detail
- Clear written and verbal communication skills in English
- Ability to work effectively in a collaborative, team-oriented environment
Competencies: - Critical thinking and intellectual curiosity
- Strong ownership of work and accountability for quality
- Ability to translate complex quantitative ideas into practical, usable solutions
- Comfort working across disciplines (quant research, engineering, risk, product)
- Interest in building robust, scalable, and well-governed analytical systems
- Innovative thinking balanced with sound judgment and practicality
Is a plus...- Exposure to machine learning and AI techniques, particularly as applied to financial or time-series data
- Experience applying AI, ML, or automation to model lifecycle and governance workflows, such as validation, back-testing, testing, monitoring, documentation, or code migration
- Knowledge of fixed income and/or equity risk factor models
- Understanding of portfolio theory and risk analytics
- Experience designing rigorous testing and back-testing frameworks
- Familiarity with building scalable and repeatable research or modeling processes
- Strong software engineering practices (clean, well-tested code)
- Experience with Unix/Linux and Git
For New York, NY Only the salary range for this position is USD$137,500.00 - USD$170,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
Our benefitsTo help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work modelBlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person - aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
