Senior Quant Researcher, Fixed Income — Data-Driven Trading

Risk Hub; New York (NY); Remote; GBP 101,000 - 123,000; Full time

Job summary

Risk Hub is seeking a Quant Researcher to drive research and implementation of trading ideas within an automated framework. You will analyze large data sets with advanced statistics to uncover opportunities and develop an in-depth understanding of market structure across exchanges and asset classes.

Prior to trading, ensure data readiness; during trading hours, monitor strategy behavior and performance, adjusting as needed. Strong quantitative background and coding ability are essential.

Qualifications

• Quantitative background: degrees in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics.
• Programming proficiency in C++, Java or Python.
• Strong communication skills and ability to work across regions.
• Ability to work well under pressure.
• Experience developing and implementing systematic strategies.

Responsibilities

• Research and implement strategies within the firm’s automated trading framework.
• Analyze large data sets using advanced statistical methods to identify trading opportunities.
• Develop a strong understanding of market structure of various exchanges and asset classes.
• Before market open, ensure data and related processes are ready for the trading day.
• During market hours, monitor behavior and performance of strategies.

Skills

Programming proficiency (C++, Java, or

Cross-regional collaboration

Work well under pressure

Developing systematic Trading ideas

Education

Mathematics

Statistics

Econometrics

Financial Engineering

Operations Research

Computer Science

Physics

Job description

Risk Hub is seeking a Quant Researcher to drive research and implementation of trading ideas within an automated framework. You will analyze large data sets with advanced statistics to uncover opportunities and develop an in-depth understanding of market structure across exchanges and asset classes.

Prior to trading, ensure data readiness; during trading hours, monitor strategy behavior and performance, adjusting as needed. Strong quantitative background and coding ability are essential.