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# Quantitative Developer - University Graduate

- **Company:** BRIDGEFRONT CAPITAL, LLC
- **Location:** Rollingwood, TX, United States
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Linux, Programming Tools, Systems Theories, Python (Programming Language), Machine Learning, Software Engineering, Model Validation, Information Technology, Build Tools, Data Pipelines
- **Published:** October 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=3b64037934f27b0e

## About the Role

* A Bachelor's degree in computer science, mathematics, statistics, physics, engineering, or another highly quantitative field, completed by the employment start date.
 * Exceptional Python programming skills and comfort working in Linux.
 * Strong foundations in probability, statistics, linear algebra, algorithms, and machine learning.
 * Ability to recognize when implementation, data-quality, or measurement issues could invalidate a research result.
 * Evidence of technical depth through substantial coursework, research, independent projects, competitions, open-source contributions, or prior work experience.
 * Intellectual flexibility: willingness to challenge assumptions, accept critical feedback, and change direction when warranted by evidence.
 * Clear written and verbal communication.
 * Experience using modern AI-assisted development tools to improve engineering and research productivity, combined with the judgment to test, validate, and take responsibility for their output.

## Description

You will build research systems and implement machine-learning methods and tools that improve how investment ideas are developed, tested, and deployed. The role combines production-quality software engineering with rigorous quantitative research. New graduates receive close mentorship while taking meaningful ownership early in their careers.

With demonstrated success, quantitative developers can advance to senior roles in quantitative development, research engineering, or technical leadership.

In this role you will:

 * Build tools and infrastructure that accelerate ML-focused feature research, experimentation, model evaluation, and strategy development.
 * Develop reliable Python research infrastructure, data pipelines, instrumentation, and parallel-computing workflows.
 * Write tested, maintainable, performance-conscious code in a Linux environment.
 * Use AI-assisted development tools to increase research and engineering productivity while independently validating their output.
 * Work directly with senior researchers and portfolio managers to turn promising research into robust investment systems.