Overview

This is a hybrid role, with the expectation that time working will regularly take place inside and outside of a company office.

This role is pivotal in supporting FCB's liquidity risk management by developing advanced financial models, performing comprehensive data analyses, ensuring compliance with regulatory standards, and collaborating with various Lines of Business to enhance FCB's liquidity strategy. You will contribute significantly to the firm's financial stability by effectively managing liquidity risk and aligning with regulatory expectations. Your work will play a crucial part in driving strategic decision-making and supporting FCB's overall success.

Responsibilities

• Build and enhance models for liquidity stress testing and cash-flow forecasting using Python, SQL, and other analytical tools.
• Develop quantitative models that support strategic decision-making and ensure adherence to regulatory standards.
• Explore new modeling approaches to improve accuracy and effectiveness in managing liquidity risk.
• Create and maintain comprehensive documentation of model methodologies, assumptions, and validation processes to ensure transparency and facilitate regulatory compliance.

• As part of the larger liquidity risk management framework, develop and implement methodologies to model the behavior of on- and off-balance sheet exposures, enhancing the firm's ability to assess and manage liquidity risks effectively
• Ensure alignment with regulatory requirements and strengthen FCB's overall liquidity risk strategy.
• Collaborate with Asset Liability Management (ALM) teams when liquidity risk considerations intersect with broader balance sheet management.

• Build and manage efficient data pipelines that deliver precise and timely liquidity risk metrics and support modeling activities.
• Generate comprehensive reports that meet regulatory requirements and support informed internal decision-making.
• Conduct detailed analyses to identify liquidity trends and emerging risks.
• Develop dynamic reporting frameworks and dashboards to provide real-time insights to leadership

• Work with cross-functional teams to ensure seamless implementation and integration of liquidity risk processes across systems
• Identify inefficiencies in workflows and develop solutions to streamline operations and enhance data accuracy.
• Facilitate the adoption of automated tools and technologies to improve operational efficiency and minimize risk across the organization.

• Ensure all models and processes align with applicable regulatory standards, including Regulation YY.
• Collaborate with second-line risk management, audit teams, and external regulatory bodies to support reviews and stress testing.
• Maintain accurate and transparent reporting in all regulatory submissions.

• Bachelor's degree in Finance, Statistics, Economics, Mathematics, Computer Science, or a related quantitative field; Master's degree preferred.
• Minimum of 1 year of relevant experience in finance or risk management; experience in liquidity risk management is highly desirable.
• Advanced proficiency in Python and SQL, with demonstrated experience in model development and data analysis.
• Strong expertise in Microsoft Excel.
• Knowledge of regulatory frameworks such as Basel III, Dodd-Frank Act, CCAR, and Regulation YY is a plus.
• Experience with data visualization and automation tools (e.g., Tableau, Power BI, Alteryx) is a plus.
• Exceptional analytical and problem-solving skills with the ability to interpret complex data sets.
• Excellent communication and collaboration skills, with experience working across teams and interfacing with external regulatory bodies.
• Detail-oriented with strong organizational skills and the ability to manage multiple projects concurrently.
• Self-motivated and proactive in identifying opportunities for improvement and driving solutions.