Senior Manager - Liquidity Risk

At PwC, our people in audit and assurance focus on providing independent and objective assessments of financial statements, internal controls, and other assurable information enhancing the credibility and reliability of this information with a variety of stakeholders. They evaluate compliance with regulations including assessing governance and risk management processes and related controls. Those in internal audit at PwC help build, optimise and deliver end-to-end internal audit services to clients in all industries. This includes IA function setup and transformation, co-sourcing, outsourcing and managed services, using AI and other risk technology and delivery models. IA capabilities are combined with other industry and technical expertise, in areas like cyber, forensics and compliance, to address the full spectrum of risks. This helps organisations to harness the power of IA to help the organisation protect value and navigate disruption, and obtain confidence to take risks to power growth.

Job Summary

PwC is seeking an experienced professional with specialized knowledge in liquidity risk management and liquidity regulatory reporting to join our Financial Services Risk & Regulatory Advisory practice. The candidate selected for this role will work closely with US-based banking clients to develop and enhance end-to-end liquidity frameworks, including internal liquidity stress testing, contingency funding plans, liquidity risk identification, limits and triggers, cash flow forecasting, intraday liquidity management, collateral management, and liquidity regulatory reporting.

Job Requirements And Preferences

Skills and responsibilities for this role include but are not limited to:

• Support clients in the enhancement of liquidity stress testing processes including data analysis, assumption development, scenario design, and methodology documentation.
• Develop and document Contingency Funding Plans (CFP), including trigger frameworks and recovery action playbooks.
• Perform liquidity risk identification specific to client risk profile and document granular risk descriptions.
• Advise clients on the development and enhancement of short and long-term cash flow forecasting methodologies including design of assumptions and variance analysis processes.
• Collaborate with treasury, risk, and finance teams to implement intraday liquidity management frameworks, including measurement of daily liquidity positions and stress metrics.
• Collaborate with treasury and treasury operations teams to enhance collateral management, movement, and monitoring practices.
• Assist in the design and development of liquidity policies, governance frameworks, and escalation protocols.
• Provide hands-on expertise on FR 2052a reporting requirements, including data sourcing, interpretation of instructions, control framework, governance, and gap remediation.
• Support liquidity risk engagements covering reporting of Liquidity Coverage Ratio (LCR), Net Stable Funding Ratio (NSFR).
• Perform analysis of large data historical data sets to aid in design of liquidity stress testing assumptions using tools such as Python, R, SQL and/or Alteryx.
• Develop Python-based liquidity risk models to support scenario analysis, stress testing, and contingency planning.
• Design and operationalize stress assumptions aligned to recovery and failure scenarios for Resolution and Recovery Planning (RRP) to meet regulatory and supervisory expectations (e.g., Fed, OCC, FDIC).
• Contribute to internal initiatives such as thought leadership, capability building, and solution development for liquidity risk and treasury transformation.
• Required Qualifications
• Bachelor’s or Master’s degree in Finance, Economics, Engineering, Mathematics, or related quantitative field. (Tier I colleges preferred)
• 5–8 years of relevant experience in liquidity risk, regulatory liquidity reporting, or treasury risk transformation.
• Preferred Qualifications
• FRM and CFA certification
• Experience working with US banking clients, particularly in liquidity regulatory transformation or treasury operating model redesign.
• Exposure to liquidity tools/platforms (e.g., QRM Liquidity, Empyrean, or custom treasury platforms) is a plus.
• Proficiency in Python for liquidity stress testing, scenario modelling, and data-driven risk analytics is preferred