Intraday Liquidity Management – Data Analytics and Forecasting, Associate

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Corporate Sector

This role focuses on developing and managing intraday liquidity analytics using AI/ML tools to forecast cash positions and outflows within a financial institution. It involves leveraging payments data, building backtesting frameworks, and collaborating with technology teams.

What you'd actually do

  1. 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.
  2. 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.
  3. Develop and maintain back testing framework aimed to improve/enhance forecast accuracy.
  4. Own and maintain governance documents supporting forecast assumptions and details of model(s) employed.
  5. Collaborate with the Product & Technology teams on further enhancements and addition of new intraday analytics and forecasts.

Skills

Required

  • Python coding
  • strong SQL skills
  • 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)
  • Databricks (e.g, notebooks, scalable data prep, productionizing repeatable analytics)
  • organized self-starter
  • quick learner
  • ability to work under pressure
  • prioritize multiple deliverables
  • bring them to closure
  • Clear and concise written and verbal communication skills
  • communicate effectively with partners across J.P. Morgan

What the JD emphasized

  • Practical experience applying ML or time-series forecasting to real operational or financial workflows

Other signals

  • AI/ML tools to forecast intraday and end-of-day cash positions
  • Develop and maintain back testing framework aimed to improve/enhance forecast accuracy
  • Practical experience applying ML or time-series forecasting to real operational or financial workflows