The role focuses on designing and implementing electronic trading algorithms for government bonds and interest rate swaps within the Fixed Income Division
Job Summary
The role focuses on designing and implementing electronic trading algorithms for government bonds and interest rate swaps within the Fixed Income Division.
Professionals will develop statistical and machine learning models for RFQ pricing, auto-hedging, risk management, and alpha research.
Morgan Stanley offers a superior foundation for building a professional career with a culture that balances personal lifestyles and perspectives.
Matching Summary
The role focuses on designing and implementing electronic trading algorithms for government bonds and interest rate swaps within the Fixed Income Division.
Skills & Requirements
Must-have
Strong foundation in probability and statistics
Proficiency in Python programming language
Experience with RFQ auto-quoting models
Solid understanding of fixed income instruments
Ability to translate trading ideas into solutions
Nice-to-have
Familiarity with Q/kdb and Java programming
Experience in other areas of electronic trading
Excellent communication skills for diverse stakeholders
Proven ability to collaborate closely with IT teams
Self-motivated and tenacious work ethic
Key Requirements
Advanced degree in quantitative field such as mathematics or computer science
Relevant academic research experience is a plus
Knowledge of financial markets and interest rate swaps