Quantitative Researcher

About the Role

We are seeking a Quantitative Researcher to be part of a compact team responsible for managing strategies through every stage—from initial concept and data analysis to implementation, deployment, and live performance monitoring. With a rapidly expanding portfolio of markets and strategies, this role comes with significant responsibility from the outset.

Key Responsibilities

• Conduct research, design, and develop market-making and systematic trading strategies, taking them from prototype to live deployment.
• Perform detailed analysis of market microstructure across various venues, each with distinct fee structures, latency, funding, and settlement characteristics, and adjust strategies accordingly.
• Create predictive models utilizing order-book, trade, funding, and on-chain data by applying statistical and machine learning techniques, accompanied by comprehensive backtesting and simulation for validation.
• Continuously monitor and refine active strategies by reviewing parameters, diagnosing profit and loss trends and inventory behaviors, while collaborating closely with traders and engineers for swift iteration.
• Support and enhance research infrastructure including simulation engines, backtesting frameworks, and data pipelines using Python and Rust.
• Assess new trading venues, financial instruments, protocols, and data sources to identify opportunities for developing novel strategies.

Candidate Profile

• Holds a degree in quantitative or technical fields such as mathematics, physics, statistics, computer science, or engineering. Advanced degrees are a plus but not mandatory.
• Possesses between zero and five years of experience in quantitative research, systematic trading, or market making within crypto or traditional financial markets. Preference is given to candidates who have completed the full strategy lifecycle—from research to live trading and post-trade analysis. Exceptional recent graduates will also be considered.
• Demonstrates deep understanding of market mechanics including order-book dynamics, adverse selection effects, inventory management, and funding risks, with the ability to differentiate genuine opportunities from backtest artifacts.
• Proficient in Python for research and analytical tasks; Rust experience is highly valued. Familiarity with C++ or Java is beneficial.
• Comfortable working with large, noisy, and irregularly spaced datasets and the statistical tools necessary for reliable inference.
• Disciplined in risk control, monitoring procedures, and maintaining detailed documentation, especially while managing multiple simultaneous strategies.
• Exhibits curiosity, autonomy, precision, and adaptability in a fast-paced, ambiguous environment while communicating effectively with both researchers and engineers.

Desirable Skills and Experience

• Practical experience providing liquidity or executing trades in centralized finance (CeFi) or decentralized finance (DeFi) settings, including platforms such as centralized perpetual swap venues, Automated Market Makers (AMMs), and on-chain order books.
• Exposure to trading derivatives beyond linear perpetual contracts, including strategies involving funding rates and basis trades.
• Knowledge of tokenized real-world assets or traditional exchange microstructure that applies to these assets.
• Professional experience using Rust in production environments, or translating research code into low-latency trading systems.
• Familiarity with exchange application programming interfaces (APIs), real-time market data feeds, and blockchain-based data extraction.
• Proven participation or success in competitive quantitative challenges such as Kaggle competitions, ICPC contests, trading competitions, or mathematical olympiads.