Job description
As the Head of Quantitative Risk Management within the Risk Infrastructure (RI) team, you will play a crucial role in leading our risk and performance management efforts. This is a strategic position suited for a proactive leader with expertise in risk management, quantitative analytics, and data infrastructure. You will spearhead initiatives to strengthen our risk systems, enhance data architecture, and support AI-driven risk insights that propel our organization forward.
In this role, you will lead a team to manage and advance the systems and data frameworks essential for comprehensive risk assessment and reporting. Your contribution will be instrumental in addressing diverse risk issues, reshaping our data architecture, and driving digital transformation across asset classes.
Key Responsibilities:
Risk Infrastructure Leadership: Provide oversight of the data and systems infrastructure necessary to support enterprise risk management activities. Ensure that risk infrastructure aligns with RPMD's goals and supports robust risk analysis and performance reporting.
Team Leadership and System Management: Lead and manage a team of system specialists responsible for maintaining and enhancing risk and performance systems. This includes overseeing daily operations and coordinating with stakeholders to align system enhancements with business needs.
Technology and Data Collaboration: Serve as the main escalation point for issues related to risk systems, working closely with the Technology Group to design and implement solutions that address user requirements and improve operational efficiency.
Data Initiatives and Standards Compliance: Actively contribute to and drive enterprise-wide data initiatives, focusing on the enhancement of data infrastructure and the establishment of best practices in data governance. Ensure that all risk infrastructure complies with internal Technology and Data policies.
Data Architecture Design: Oversee the design and development of RPMD's data architecture, including analytical data marts and data services, ensuring alignment with the firm's broader data strategy.
Stakeholder Engagement: Build strong relationships with senior stakeholders, including risk managers, front office, and corporate services. Communicate complex issues effectively, resolve key challenges, and ensure alignment of risk management objectives across departments.
Requirements:
Educational Background: Bachelor's Degree in Banking & Finance, Engineering, Data Science, or a related field. Professional certifications such as FRM (Financial Risk Manager) or advanced quantitative finance training (e.g., MFE) are highly desirable.
Experience: A minimum of 10 years of experience in risk management roles involving risk methodologies, data analytics, production, and data management in a financial institution setting.
Technical Knowledge: Strong understanding of financial instruments across asset classes (equities, fixed income, commodities, derivatives) with additional exposure to private market assets (e.g., private equity, real estate) being beneficial.
Quantitative and Data Expertise: Solid experience with risk methodologies, market and credit risk analytics, and familiarity with financial data sets, including reference data, transactions, and portfolio valuations. Knowledge of data modeling for operational and analytics purposes is essential.
Process and Systems Management: Proven experience in designing and managing risk systems with a strong process orientation. Experience in handling large-scale data migration projects is a plus.
Communication and Stakeholder Management: Exceptional communication skills, with a track record of engaging and influencing senior management, Technology, and Data partners. Ability to articulate complex technical issues clearly and build consensus among stakeholders.
Leadership Skills: Demonstrated team management experience, with the ability to inspire, develop, and manage a high-performing team.
