Systematic Credit Quantitative Researcher
$500,000–$1,000,000 year
On-site · New York City, New York, United States
Job Summary
Develop quantitative models for Systematic Credit using probability theory, statistics, and machine learning to interpret credit markets and generate alpha; refine and design trading strategies, moving into live deployment, calibrating parameters, and reacting to unusual market conditions. Collaborate closely with researchers and engineers across the execution infrastructure to optimize performance. Proficiency with Python for large datasets is required, with C++ or another systems-level language as a bonus. The role is based in New York City, with relocation expenses covered, and requires working five days per week at the NYC office. The environment is highly collaborative and fast-paced, with opportunities to influence live trading strategies and P&L outcomes.
Required Qualifications
- Experience within Systematic Credit is highly desirable
- Sharp analytical thinkers who enjoy reasoning through complex problems
- Strong communicators who thrive in a fast-moving environment with cross-team collaboration
- Comfortable working with sizable datasets in Python; background in C++ or another systems-level language is a nice bonus
- Self-starters who pick things up quickly and stay curious under a demanding pace
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