Treasury Liquidity Data Analyst

Huntington National Bank•Columbus, OH

7h•Onsite

About The Position

The Treasury Liquidity Data Analyst reports to the Liquidity Manager and helps modernize the team's data, analytics, and operating capabilities. Working within the bank's first-line liquidity risk function, the analyst uses SQL, Python, automation, and applied artificial intelligence to improve how liquidity data is sourced, validated, analyzed, measured, and communicated. The role identifies manual or inefficient processes, develops scalable solutions, and strengthens recurring analytics and reporting through well-controlled automation. The analyst builds and supports AI-enabled tools and agents that accelerate research, exception identification, documentation, and management reporting while maintaining appropriate human review, data governance, information security, and change-control standards. The successful candidate will develop an understanding of liquidity monitoring, cash flow forecasting, contingency funding, and balance-sheet behavior, and brings strong technical curiosity and a continuous-improvement mindset.

Requirements

Bachelor's degree in Finance, Accounting, Economics, Data Analytics, Computer Science, Information Systems, Mathematics, Statistics, or a related field, or an equivalent combination of education and experience.
Two or more years of relevant experience in data analytics, automation, financial analysis, Treasury, banking, financial risk, consulting, financial technology, or a related discipline.

Nice To Haves

Two to four years of relevant professional experience in data analysis, process automation, financial datasets, or risk and Treasury applications.
Working proficiency with SQL and Python for data analysis and automation, including querying, reconciling, and validating data across datasets; using libraries and tools such as pandas, NumPy, Jupyter, and Git; and developing reusable, well-documented code and data-quality checks.
Experience building automated data pipelines, reconciliations, exception reports, dashboards, controls, or management information, and working with balance-sheet, deposit, funding, cash flow, general-ledger, or other financial datasets.
Practical familiarity with generative AI, including experience developing, prototyping, or supporting AI-enabled workflows or agents using Python, APIs, or approved enterprise tools, and exposure to large language models, retrieval-augmented generation, prompt design, or agent frameworks.
Demonstrated ability to evaluate manual or inefficient processes, translate business needs into technical requirements, and implement controlled, sustainable improvements.
Exposure to Treasury, liquidity risk, asset-liability management, cash flow forecasting, contingency funding, stress testing, or regulatory reporting.
Awareness of data governance, responsible AI, model risk, information security, software-development controls, or change-management practices in a regulated environment.
Proficiency with Microsoft Excel and PowerPoint, and familiarity with data visualization or business intelligence tools.

Responsibilities

Use SQL and Python to source, combine, transform, validate, and analyze balance-sheet, deposit, funding, cash flow, and liquidity data from multiple systems.
Automate recurring workflows, reconciliations, controls, analysis, and management reporting to reduce manual effort, improve scalability, and ensure timely, repeatable execution.
Assess existing processes and data flows, identify root causes of inefficiency and data-quality issues, and implement practical, well-documented improvements with measurable outcomes.
Design, prototype, test, and maintain AI-enabled tools and agents that support research, data validation, exception identification, workflow orchestration, documentation, and insight generation.
Apply disciplined governance to data, automation, and AI solutions, including requirements documentation, source-to-output traceability, validation and testing, human review, access controls, change management, and ongoing performance monitoring.
Develop clear analytical outputs and visualizations that explain trends, exceptions, and key drivers to Treasury leadership and cross-functional partners.
Apply analytical and automation capabilities to liquidity monitoring and metrics, long-term cash flow forecasting, Contingency Funding Plan activities, control execution, and regulatory reporting support.