Liquidity Risk Management Jobs in North Carolina

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates' physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description:
This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products.

Responsibilities:

• Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
• Supports the planning related to setting quantitative work priorities in line with the bank's overall strategy and prioritization
• Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
• Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
• Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
• Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
• Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
• Work closely with Technology and data engineering teams to design and implement robust systems and infrastructure that run and scale the developed liquidity models and analytics
• Participate in system testing, ensure model integration into enterprise platforms, and identify enhancements to data pipelines and analytical tools supporting liquidity risk management
• Create and maintain comprehensive technical documentation for all liquidity stress methodologies, data processes, and assumptions

Required Qualifications:

• Quantitative & Analytical Skills: Proven ability to analyze and manipulate large datasets with strong attention to detail and data integrity. Experience applying statistical or quantitative methods to real-world financial questions.
• Financial & Liquidity Knowledge: Fundamental understanding of liquidity risk metrics (e.g., cash flow forecasting, liquidity coverage, or stress testing), balance sheet structure, and financial market dynamics. Familiarity with banking products and liquidity-related regulatory concepts.
• Project & Time Management: Excellent organizational skills with the ability to manage multiple priorities, meet deadlines, and adapt in a time-sensitive environment without sacrificing quality. Self-motivated and able to work independently with minimal supervision.
• Communication: Strong written and verbal communication skills, including the ability to distill complex quantitative analyses into clear insights for technical and non-technical stakeholders. Experience with formal presentations or reporting of analytical findings.
• Teamwork: Demonstrated ability to collaborate effectively with cross-functional teams (e.g., technology, risk, finance) and proactively share knowledge.

Desired Qualifications:

• Advanced Technical Skills: Proficiency in Python programming for data analysis, statistical modeling, and automation; strong knowledge of SQL and relational databases for complex data extraction and transformation tasks; experience with data analytics and workflow tools such as Alteryx; and familiarity with data visualization platforms like Tableau to create intuitive dashboards and reports.
• Quantitative Modeling & Statistics: Experience developing or using quantitative models (particularly in risk or liquidity contexts), statistical analysis techniques (e.g., regression analysis, scenario simulation, Monte Carlo methods), or working with large-scale data frameworks.
• Liquidity & Regulatory Expertise: Background in liquidity risk management or regulatory liquidity reporting (such as LCR, NSFR, FR 2052a, or other liquidity stress testing processes) is highly desirable. Knowledge of balance sheet management and ALM (Asset-Liability Management) practices is a plus.
• Advanced Education & Certifications: Master's degree in a relevant quantitative discipline (Finance, Mathematics, Financial Engineering, Data Science, etc.) or professional certifications like FRM (Financial Risk Manager) or CFA are strongly preferred, indicating advanced analytical training and commitment to the field.

Skills:

• Critical Thinking
• Quantitative Development
• Risk Analytics
• Risk Modeling
• Technical Documentation
• Adaptability
• Collaboration
• Problem Solving
• Risk Management
• Test Engineering
• Data Modeling
• Data and Trend Analysis
• Process Performance Measurement
• Research
• Written Communications

Minimum Education Requirement: Master's degree in related field or equivalent work experience

Shift:

Hours Per Week: