Core Risk Governance, RQA, Associate

Business Overview

Understanding and managing risk is the cornerstone of BlackRocks approach to responsible investing. The Risk & Quantitative Analysis (RQA) group provides independent oversight of BlackRocks fiduciary and enterprise risks. Our mission is to advance the firms risk management practices and to deliver independent riskexpertiseand constructivechallengesto drive better business and investment promotes BlackRock as a leader in risk management by providing independent top-down and bottom-up oversight to helpidentifyinvestment counterparty operational regulatory technology and third-party risks.

RQA is committed to investing in our people to increase both individual enablement and a strong collaborative environment. As a global grouplocatedall around the world our goal is to create a culture of inclusion which encourages teamwork innovation diversity and the development of our future leaders. We actively engage in discussions on career growth and work with team members to understand how personal passions and strengths connect with our purpose.

Role Description:

Core Risk Governance responsible for delivering firmwide risk oversight governance and control effectiveness across investment strategies and asset classes. The team playsa central rolein ensuring the integrity of risk frameworks portfolio setup controls and governance processes byleveragingdata advanced analytics automation and AIenabled solutions at scale.

The function focuses on centralising risk governance activities strengthening preventive controls and embedding technologydriven oversight across the investment lifecycle. By building standardized data frameworks deploying AIand analyticsbased controls and delivering transparenttimelyreporting Core Risk Governance enables consistent decisionmaking and robust escalation across the platform.

The team partners closely with Investment Risk Technology Data Compliance and Control functions to modernise risk governancemoving from manual fragmented processes to systematic scalable and explainable AIenabled solutions that enhance risk visibility control effectiveness and operational resilience across Core RM.

Key Job Responsibilities:

• Architect build and scale AI driven solutionsfrom ideation and proof of concept to production deploymentto transform risk and data processes through advanced automation intelligent exception management and predictive insights.

• Write production grade code in Python to build data pipelines automation frameworks analytics libraries and AI/ML components; ensure solutions are maintainable tested and deployable.

• Design build andmaintainresilient data pipelines (batch and streaming) with strong engineering controls including SLAs dependency management backfills replay/re ingest capabilities and automatedalerting..

• Define and enforce data persistence schema standardization lineage and metadata management ensuring traceability auditability andlong termreliability of analytical outputs.

• Implement data quality and control frameworks including automated validation checks reconciliation to source threshold based monitoring and structured exception queues with clear escalation path.

• Develop scalable analytics and reporting solutions translating complex datasets into clear explainable and decision ready outputs for senior stakeholders.

• Partner closely with cross functional teams (technology data risk compliance) to embed governance controls and resilience directly into technical and AI enabled solutions

• Continuouslydriveautomation process efficiency and platform resiliencereducing manual intervention while improving accuracy timeliness and scalability.

Experience Skills and Qualification:

• Bachelors/Mastersdegree in Engineering Computer Science Data Science Mathematics or a related quantitative discipline.

• 36 years of handson experience in Pythonbased analytics and AI/ML including building data pipelines developing models/LLM/agent workflows and integrating outputs into business processes.

• Strong data engineering and data governance foundations including data quality controls lineage metadata management and controlframeworks..

• Proficiencyin advanced analytics with experiencewith techplatforms

• Ability to design and implement reporting solutions for portfolio monitoring stress testing and regulatory compliance.

• Strong stakeholder management and communication skills to collaborate across investment technology and compliance teams.

• Experience in automation and process optimization for reporting and analytics workflows.