Rapidly prototype, build, and iterate on quantitative research tools, trading applications, and AI-driven systems, taking ideas from initial concepts to functional implementations
Leverage AI coding agents, LLMs, and modern development frameworks to accelerate experimentation, engineering, testing, and deployment
Experience
Proven experience in research within the financial services industry, particularly in investment banking or asset management
Strong background in finance, with a focus on investment strategies, risk analysis, and quantitative modeling
Proficiency in advanced mathematics, statistical analysis, and programming languages such as Python, R, or MATLAB
Familiarity with financial markets, instruments, and trading platforms is highly desirable
Demonstrated ability to analyze complex data sets and develop innovative solutions for investment challenges
Prior experience in developing or implementing algorithmic trading systems is a plus
Hands-on experience designing and orchestrating agentic workflows using LLMs, AI coding agents, tool integrations, and automated execution pipelines
Demonstrated ability to rapidly prototype and build end-to-end software applications, research infrastructure, and data-driven products
Experience with modern software development practices, including APIs, version control, testing, cloud deployment, and iterative product development
Ability to independently translate abstract research ideas into working prototypes, production-ready tools, and scalable systems
This role is ideal for individuals passionate about applying quantitative methods to finance, eager to contribute to cutting-edge trading strategies, and committed to continuous learning within a fast-paced environment.