Quantitative Trading Systems Engineer

Referment; Salt Lake City (UT); On-site; USD 120,000 - 190,000; Full time

Job summary

Referment is a quantitative investment firm seeking a developer to build the software and research frameworks behind its trading activity. This role blends software engineering with quantitative problem-solving, and the exact project mix will depend on the team.

You could work on low-latency market-data delivery, cloud-based simulation environments, or a robust research framework for new asset classes, using Python and C++ across on-premises and cloud environments.

Qualifications

• Build reliable software and frameworks used in quantitative research and trading.
• Deliver fast market data into trading systems where performance is critical.
• Develop integrated research and execution frameworks for fast predictors.
• Create simulation and research tooling for cloud environments.
• Support the development of research infrastructure for new asset classes.
• Work across Python and C++ systems deployed both on-premises and in the cloud.

Responsibilities

• Build reliable software and frameworks used in quantitative research and trading.
• Deliver fast market data into trading systems where performance is critical.
• Develop integrated research and execution frameworks for fast predictors.
• Create simulation and research tooling for cloud environments.
• Support the development of research infrastructure for new asset classes.
• Work across Python and C++ systems deployed both on-premises and in the cloud.

Skills

Strong programming ability

Quantitative acumen

Experience with Python

Experience with C++

Tools

Python

C++

Job description

Referment is a quantitative investment firm seeking a developer to build the software and research frameworks behind its trading activity. This role blends software engineering with quantitative problem-solving, and the exact project mix will depend on the team.

You could work on low-latency market-data delivery, cloud-based simulation environments, or a robust research framework for new asset classes, using Python and C++ across on-premises and cloud environments.