Quantitative Trading & Research – Credit Portfolio – Associate

The Quantitative Trading & Research Portfolio team specializes in building data-driven, AI-powered tools that empower traders to act quickly and manage risk more effectively. Operating at the intersection of machine learning, real-time data analysis, and quantitative finance, the team transforms complex data into actionable insights with immediate impact on trading and risk management.

Job Summary:

As an Associate in the Quantitative Trading & Research Portfolio team Data Strategist, you will build data driven, AI-powered tools to help our traders act faster and manage risk smarter. You'll work at the intersection of machine learning, real-time data analysis and quantitative finance to turn complex data into clear, actionable insights.  Your work will have immediate, visible impact on how we trade and manage risk.

Job responsibilities:

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

Required qualifications, capabilities, and skills:

• 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; exposure to multi-agent AI workflow is a plus.
• 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.

Preferred qualifications, capabilities, and skills:

• 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.