Senior Quant Researcher: Automated Trading & Data Analysis

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

Job summary

Risk Hub is seeking a quantitative researcher to research and implement trading strategies within our automated framework. You will analyze large data sets with advanced statistical methods to identify opportunities and constantly test robustness.

You will build a deep understanding of market structure across exchanges and asset classes, work with intraday bar data, and present results to management with clear recommendations for next steps and improvements.

Qualifications

• Quantitative background in Mathematics, Statistics, Econometrics, Financial Engineering, OR, CS or Physics.
• Proficiency in at least one major language (C++, Java, Python).
• Strong communication and cross-regional collaboration skills.
• Ability to work well under pressure.
• Familiarity with liquid non-equity asset classes (futures, FX, cash treasuries).
• Experience with intraday bar data and intraday trading research.

Responsibilities

• Research and implement strategies within automated trading framework.
• Analyze large data sets using advanced statistical methods to identify opportunities.
• Develop understanding of market structure across exchanges and asset classes.
• Critically verify results for statistical significance and robustness.
• Present results to manager and discuss improvements and next steps.

Skills

Strong communication

Work under pressure

Statistical analysis

Data analysis

Education

Mathematics

Statistics

Econometrics

Financial Engineering

Operations Research

Computer Science

Physics

Tools

C++

Java

Python

Job description

Risk Hub is seeking a quantitative researcher to research and implement trading strategies within our automated framework. You will analyze large data sets with advanced statistical methods to identify opportunities and constantly test robustness.

You will build a deep understanding of market structure across exchanges and asset classes, work with intraday bar data, and present results to management with clear recommendations for next steps and improvements.