Quant Trader, FI/Credit & ETFs — End-to-End Ownership

Selby Jennings; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Selby Jennings is partnering with a world-leading quantitative trading and market-making firm to hire Quant Traders for a Fixed Income / Credit PT & ETF trading team.

The role spans idea generation through research, portfolio construction, risk management, and live execution in a collaborative, meritocratic environment. Ideal candidates have 1–4 years in trading or research, strong quantitative skills, Python programming, and a passion for financial markets.

Qualifications

• Bachelor's or Master's in Mathematics, Statistics, Physics, Computer Science, Engineering, Operations Research, or another highly quantitative STEM discipline.
• Strong quantitative and analytical problem-solving abilities.
• Programming experience in Python.
• Demonstrated interest in financial markets and systematic decision-making.
• Ability to thrive in a fast-paced, highly collaborative trading environment.

Responsibilities

• Develop, test, and implement quantitative trading strategies across fixed income, credit, and ETF markets.
• Generate alpha through analysis of market, trading, and alternative datasets.
• Monitor and manage live risk across active portfolios.
• Research new signals, portfolio construction techniques, and execution methodologies.
• Partner closely with traders, researchers, and technologists to deploy and enhance strategies.
• Evaluate market structure, liquidity dynamics, and relative value opportunities.
• Continuously refine models and trading processes to improve performance.

Skills

Python

Quantitative skills

Analytical thinking

Collaboration

Education

Bachelor's or Master's in STEM

Job description

Selby Jennings is partnering with a world-leading quantitative trading and market-making firm to hire Quant Traders for a Fixed Income / Credit PT & ETF trading team.

The role spans idea generation through research, portfolio construction, risk management, and live execution in a collaborative, meritocratic environment. Ideal candidates have 1–4 years in trading or research, strong quantitative skills, Python programming, and a passion for financial markets.