Quantitative Developer - New Grad

Position Overview

Key Responsibilities

• Strategy Lifecycle Support: Participate in the full lifecycle of quantitative strategy implementation, focusing on code optimization, deployment, order execution tracking, policy compliance, and risk control mechanisms.
• Research Tooling & Backtesting: Work closely with the research team to develop and enhance strategy research tools on our in-house backtesting platform, tailoring them to their specific use cases.
• Live Operations & Reliability: Contribute to the development and maintenance of live trading processes, continuously improving the production quality and reliability of strategies through robust technical solutions.
• Infrastructure Integration: Collaborate with the engineering team to implement core components of our distributed systems, data platforms, and trading infrastructure, ensuring your code directly supports both research and live trading performance.
• Feature Iteration: Collaborate with senior developers to implement, test, and iterate on execution algorithms and trading features based on research models.

Required Qualifications & Skills

• Educational Background: Degree in Computer Science, Engineering, Mathematics, Physics, or a highly quantitative field.
• Strong Coding Fundamentals: Clean, proficient coding skills in Python (for data analysis and tooling) and C++ (for core systems logic). Solid understanding of data structures, algorithms, and software design principles.
• Quantitative Competency: Strong grounding in probability, statistics, and data analysis; comfortable working with large datasets and debugging complex log files.
• Eagerness to Learn: A deep, demonstrable interest in financial markets, electronic execution, and market microstructure.
• Collaborative Mindset: Excellent communication skills with the ability to working effectively across different disciplines (researchers, core engineers, and traders).

Preferred/Nice-to-Have

• Outstanding performance in competitive programming contests such as NOI or ICPC.
• Experience with distributed systems, high-performance computing (HPC), or handling large-scale tick data.
• Familiarity with connectivity protocols (e.g., FIX, native exchange APIs).
• Publications in top-tier CS or Statistics journals/conferences.
• Award-winning participant in Kaggle machine learning competitions.
• Internship or work experience in proprietary trading firms, hedge funds, or leading tech companies.