Intraday Liquidity Management – Data Analytics and Forecasting, Associate

The Intraday Liquidity (IDL) Management function sits within Corporate Treasury and predominantly leverages a proprietary, real-time application under the same name, Intraday Liquidity (IDL), to manage the firm’s USD intraday liquidity, mainly driven by global cash & payments activity. The team interacts with global regulators, clearing houses, Financial Market Infrastructures, Wholesale Payments Technology, Treasury Funding, Liquidity Strategy, Liquidity Management, Liquidity Risk Management, and the lines-of-business teams to maintain and enhance the firm’s intraday liquidity capability. As a member of the IDL team within North America Treasury, you will be tasked with being the first line of defense for firmwide IDL risk, engaging with lines of business & operations in active IDL management. More importantly, in this role, you will be responsible for developing and managing intraday liquidity analytics, using AI/ML tools to forecast intraday and end-of-day cash positions, as well as peak outflows to manage Firmwide IDL limits.

Use Python and AI/ML tools to publish a daily forecast with commentary on intraday flows across key central bank balances, payment channels and business lines. Leverage Firmwide payments data to derive analytical insights on intraday cash flow patterns in support of early detection of drivers for end-of-day central bank balance movements. Develop and maintain back testing framework aimed to improve/enhance forecast accuracy. Own and maintain governance documents supporting forecast assumptions and details of model(s) employed. Collaborate with the Product & Technology teams on further enhancements and addition of new intraday analytics and forecasts. Manage USD IDL risk across the central bank balance and bilateral counterparty flows. Required Qualifications, Skills, and Capabilities: Bachelors’ degree required. At least 2 years of full-time experience in Data Science/Analytics, Software Engineering, and/or Financial Services. Python coding (required) & strong SQL skills, with the ability to translate data into clear business narratives. Practical experience applying ML or time-series forecasting to real operational or financial workflows (feature engineering, modeling, performance monitoring, explainable outputs). An organized self-starter and quick learner with the ability to work under pressure, prioritize multiple deliverables, and bring them to closure. Clear and concise written and verbal communication skills, with the ability to communicate effectively with partners across J.P. Morgan. Preferred Qualification, Skills, and Capabilities: Databricks experience is preferred (e.g, notebooks, scalable data prep, productionizing repeatable analytics)