Join the Treasury and Chief Investment Office (TCIO), a team at JPMorgan that is responsible for firm-wide asset and liability management for one of the world’s largest global financial institutions, managing a $2.5 trillion balance sheet, which includes over $900 billion in loans and $1.4 trillion in deposits. Positioned at the center of the firm, TCIO directly influences the composition of the firm’s balance sheet and the activities of its main LOBs: Asset Management (AM), Commercial & Investment Bank (CIB) and Consumer & Community Banking (CCB).

As a Liquidity Risk Reporting Analyst in the Corporate Treasury Middle Office (CTMO), part of the TCIO organization, you will support the Firm’s daily external liquidity reporting and be part of a team responsible for overseeing the operating model that supports data aggregation used in the firm’s risk reporting process (e.g., balance sheet details, forecasts, and assumptions). This includes executing key data integrity controls, reconciliations, adjustments, and analytics. You will also coordinate the production of several firm-wide, LOB, and legal entity-level risk reports (e.g., 6G, LCR, Stress) by agreed deadlines. You will also be involved in collaborating with global contacts to quickly research and explain variances in key risk measures and facilitating sign-off by senior risk stakeholders before report distribution internally and to regulators.

Job Responsibilities:

• Review, adjust, and attest to the quality of liquidity risk data daily across all entities in the firm.

• Perform product reconciliations and assist with daily balance sheet variance analysis.

• Prepare, analyze, and provide commentary for internal and external reports to stakeholders.

• Conduct data analysis to identify and implement business validation rules to support the transition to an exception-based operating model.

• Identify improvements and leverage available toolsets (Alteryx, Tableau, Excel, Python) to own and implement changes through to completion.

• Determine business drivers behind variances and communicate impacts to partner groups such as Liquidity Risk Management and Liquidity Management.

• Support LRI tech/business enhancements and assist in technology-related developments, ensuring appropriate prioritization and end-user testing.

• Continually identify and enhance the overall control environment and operating model across core operational activities, improving timeliness and reducing operational risk to the firm.

• Partnering with internal data source providers and risk stakeholders across all lines of business to complete data investigations and resolve data quality issues, aiming to improve the timeliness and accuracy of all risk reporting continuously.
• Responding to internal or regulatory requests to complete ad hoc data analysis or produce custom reports as needed.

• Prepare key performance indicators or metrics and present them to senior management.

Required Qualifications, Skills, and Capabilities:

• 1+ years of experience in financial operations, specifically in financial reporting, balance sheet analysis, and/or asset and liability or liquidity management.

• Strong analytical skills, including the ability to conduct data investigations and summarize findings clearly and meaningfully.

• Proven leadership experience, including the ability to facilitate project and process improvements across a large organization.

• Strong technical leadership with hands‑on depth in SQL and Python; advanced Excel skills and proficiency with Tableau and Alteryx.

• Independent critical thinking, problem-solving, and decision-making abilities.

• Ability to work under pressure, prioritize, multitask, and bring tasks to completion.

• Organized and able to execute responsibilities with minimal supervision.

• Strong written and verbal communication skills, with the ability to prepare executive-level presentations.

Preferred Qualifications, Skills, and Capabilities:

• Experience with SQL, Python/VBA, or data visualization tools such as Tableau is a plus.

• Bachelor’s degree required; advanced degree in Finance, Data Science, Computer Science, or related field preferred. Relevant certifications in cloud, data engineering, or ML/AI are advantageous.