About this roleWe are seeking a VP-level Data Lead to drive the data domain supporting global multi-factor Portfolio Risk models across fixed income and equity.
This role is responsible for end-to-end execution and ownership of data quality, validation, and usability across the modeling data lifecycle. The VP will partner closely with modeling, engineering, and upstream data teams to ensure that data powering portfolio risk models is robust, well-governed, and aligned with modeling requirements.
The role combines strategic judgment with hands-on execution, with an initial focus on model input data onboarding and quality control, expanding over time to derived data, QC frameworks, and integration of new datasets.
Domain & Data Scope- Market data (prices, yields, spreads, returns) across regions and time zones
- Firm fundamentals and issuer-level financial metrics
- Bond-level characteristics and reference/security master data
- Fixed income analytics such as durations and spreads
- Equity returns, factor inputs, and cross-asset pricing series
Scope also includes:
- Derived model data (factor exposures, covariance matrices, risk decompositions)
- Model validation metrics and QC monitoring frameworks
- Research and exploratory datasets, including structured and unstructured sources
Key ResponsibilitiesData Domain Execution & Ownership- Own the data domain for portfolio risk models, ensuring high standards of data quality and usability
- Ensure data meets requirements for accuracy, completeness, consistency, and timeliness
- Define and evolve scalable QC frameworks aligned with modeling needs
- Drive improvements in data integration into modeling workflows
Quality Control & Validation- Design and implement data validation rules and QC logic
- Establish monitoring across input and derived model data
- Ensure traceability, documentation, and reproducibility of model data
- Prioritize improvements based on impact to model performance and stability
Cross-Functional Delivery- Partner with portfolio risk modeling teams to translate requirements into data solutions
- Collaborate with data engineering teams to define and implement data pipelines
- Engage with upstream data providers to improve data quality and reliability
- Drive resolution of data issues across teams with strong ownership
Data Evolution & Research Enablement- Lead onboarding and evaluation of new datasets for modeling and research
- Define governance approaches for structured and unstructured data integration
- Support adoption of advanced techniques (including AI/ML where relevant)
Leadership & Communication- Drive execution across global, cross-functional stakeholders
- Provide clear, structured updates on data quality, risks, and initiatives
- Promote accountability and strong execution standards across partners
Experience- 8-12+ years supporting data in quantitative modeling, risk, or analytics environments
- Strong familiarity with global fixed income and/or equity datasets
- Experience driving data initiatives across multiple teams and workflows
Required Skills- Deep understanding of data lifecycle, QC frameworks, and validation processes
- Strong grasp of portfolio risk modeling data requirements
- Ability to prototype and validate data logic (Python/SQL or similar)
- Strong stakeholder management and execution focus
- High ownership, attention to detail, and delivery mindset
What Success Looks Like- Data supporting models is high quality, well-governed, and consistently reliable
- QC frameworks are robust, scalable, and aligned with modeling use cases
- Data onboarding is efficient and integrated into modeling workflows
- Cross-team data initiatives are delivered with clear ownership and outcomes
- Modeling teams experience smooth, predictable data workflows
For New York, NY Only the salary range for this position is USD$170,000.00 - USD$225,000.00 . 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.
Guidance on AI use for candidatesAt BlackRock, AI has long been part of how we work - enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we've provided
guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
