Liquidity Analyst Jobs (NOW HIRING)

This role is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key tasks include developing new models, analytic processes, or system approaches; creating technical documentation; and working with technology staff in the design and implementation of systems that run these models.

• Perform end‑to‑end market risk stress testing, including scenario design, implementation, results consolidation, internal and external reporting, and analysis of stress scenario results to better understand key drivers.
• Support planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization.
• Identify continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, provide critical feedback on technical documentation, and bring effective challenges on model development/validation.
• Support model development and model risk management in respective focus areas to meet business requirements and the enterprise’s risk appetite.
• Provide 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.
• Work closely with model stakeholders and senior management to communicate submission and validation outcomes.
• Perform statistical analysis on large datasets and interpret results using both qualitative and quantitative approaches.
• Collaborate 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.

• Quantitative & Analytical Skills: Proven ability to analyze and manipulate large datasets with strong attention to detail and data integrity, and 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, and 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.
• Minimum Education Requirement: Master’s degree in a related field or equivalent work experience.

• 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.
• 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.
• Key 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.

Shift: 1st shift (United States of America) | Hours Per Week: 40