Quantitative Trading & Research – Credit Portfolio – Associate

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Commercial & Investment Bank

Build AI agentic workflows and machine learning models for risk monitoring, signal generation, and forecasting in a quantitative trading environment. Develop real-time data pipelines and deliver actionable insights to traders and risk partners.

What you'd actually do

  1. Design, build, and deploy AI agentic workflows to enhance risk monitoring, signal generation, and control processes for the trading desk.
  2. Develop real-time data pipelines integrating market and reference data to power intraday risk analytics and scenario analysis.
  3. Implement machine learning models for risk forecasting, anomaly detection, market pattern identification and liquidity estimation.
  4. Create intuitive applications and dashboards that deliver actionable risk insights to traders and risk partners.
  5. Collaborate with traders, quantitative researchers, risk teams, and technologists to translate business needs into resilient, well-documented solutions.

Skills

Required

  • Advanced degree in a quantitative field (Computer Science, Engineering, Mathematics, Physics, Statistics, or Financial Engineering), or 3 years of experience in quantitative research, data analytics, or a related technical role.
  • Hands-on experience in data analytics and machine learning
  • Strong programming skills with proficiency in numerical and machine learning libraries.
  • Strong analytical and problem-solving skills, with the ability to communicate complex ideas clearly to business partners.

Nice to have

  • exposure to multi-agent AI workflow
  • Familiarity with trading concepts, hedging, and risk measures.
  • Experience with real-time systems, event streaming, or time-series data.
  • Experience with UI design and visualization tools.

What the JD emphasized

  • AI agentic workflows

Other signals

  • AI-powered tools
  • machine learning
  • real-time data analysis
  • quantitative finance
  • AI agentic workflows
  • risk monitoring
  • signal generation
  • control processes
  • risk forecasting
  • anomaly detection
  • market pattern identification
  • liquidity estimation
  • actionable risk insights