We are seeking candidates with a strong quantitative background and hands-on programming experience. A Master’s degree in a quantitative field (e.g., Mathematics, Computer Science, Statistics, Physics) or equivalent professional experience is preferred. Candidates should have at least 2+ years in a quantitative, data science, or algorithmic role and demonstrate strong problem-solving abilities with the capacity to explain complex concepts to non-technical stakeholders. Proficiency in Python is essential, with the ability to move between research notebooks (e.g., Jupyter) and production-grade code. Solid SQL skills (including joins, aggregations, window functions, and case logic) and experience working with complex JSON data are required. Comfortable working in a Linux-based environment, including Docker, and familiarity with AWS services (EC2, SageMaker, AWS CLI, S3 workflows) are highly desirable. A natural curiosity about markets and a track record of building trading strategies, backtests, simulations, or optimization models—whether professionally or personally—will help you excel in this role. You should be a creative thinker who thrives on collaboration with engineers and analysts to deliver measurable impact on P&L and risk controls.