Risk Engineer: Build In-House Trading Risk Models

jobply; New York (NY); On-site; USD 200,000 - 300,000; Full time

Job summary

Hudson River Trading (HRT) in New York City is seeking a Risk Engineer to join our Risk team. You will build out our risk function and manage all aspects of risk faced by HRT, gaining exposure to the fast-paced world of electronic trading.

The ideal candidate brings strong quantitative skills, knowledge of risk management, and the ability to work both independently and with a team. You will develop factor risk models, ingest large data sets, and communicate findings to investment teams.

Qualifications

• B.S. in Mathematics, Physics, CS, or Statistics required.
• 2–5 years of quantitative analyst experience.
• Strong knowledge of linear algebra, probability, statistics.
• Proficient in Python and Linux.

Responsibilities

• Build and enhance in-house factor risk models for equities.
• Customize vendor market risk models.
• Research and build new models for trading and risk management.
• Work with risk managers to enhance tail risk estimation for scenarios.
• Ingest, evaluate, transform large data sets relevant to risk and performance analysis.
• Design and implement performance analytics and risk decomposition applications.
• Work with developers to productionize risk models and risk management tools.
• Enhance and maintain the risk production codebase.
• Communicate with investment teams.

Skills

Mathematics

Statistics

Probability

Communication

Education

B.S. in Mathematics / Physics / CS / Statistics

Tools

Python

Linux

Job description

Hudson River Trading (HRT) in New York City is seeking a Risk Engineer to join our Risk team. You will build out our risk function and manage all aspects of risk faced by HRT, gaining exposure to the fast-paced world of electronic trading.

The ideal candidate brings strong quantitative skills, knowledge of risk management, and the ability to work both independently and with a team. You will develop factor risk models, ingest large data sets, and communicate findings to investment teams.