Quant Trader

About the role

This role focuses on developing and refining automated trading strategies. The Quant Trader will be responsible for creating logic that synthesizes global data into fair-value anchors and dynamic spreads, as well as building self-correcting models to adjust quotes based on exposure. A key part of the work involves implementing high-velocity protocols to mitigate adverse selection and information asymmetry.

The position requires defining logic for managing risk, including internal warehousing versus external hedging. It also involves translating mathematical strategies into scalable requirements for engineering teams. Success in this role means establishing operational boundaries and automated thresholds for the trading engine, and providing technical leadership during high-leverage events.

The ideal candidate will have a deep understanding of probability and binary contracts, viewing every event as a shifting probability curve. Experience in designing production-ready trading systems, from data ingestion to automated execution, is essential. The role also demands a proven track record in deploying predictive models that learn from market microstructure and price velocity.

The listed salary range for this position is between $120,000 and $200,000 USD.

Skills that matter here

• Quantitative Fluency: This skill is crucial for understanding probability and binary contracts, treating all market events as dynamic probability curves.
• Pipeline Design: This skill is needed to build production-ready trading systems, covering everything from data intake to automated trade execution.
• Applied Data Science: This skill is used to deploy predictive models that learn from market microstructure and price velocity.
• Systems Integrity: This skill ensures the creation of error-tolerant interfaces that maintain stability even under extreme data throughput.

Who this role suits

• A person who thinks in terms of probabilities and dynamic shifts rather than fixed outcomes.
• Someone with a practical background in building and deploying automated trading systems.
• An individual who can translate complex mathematical concepts into actionable engineering requirements.
• A professional who thrives under pressure and can provide technical guidance during critical market events.

From the employer

Responsibilities:

• Autonomous Valuation: Engineer the logic synthesizing global data into fair-value anchors and dynamic spreads.
• Inventory Skewing: Build self-correcting models that adjust quotes based on exposure to incentivize book-balancing.
• Defensive Design: Implement high-velocity protocols to mitigate adverse selection and information asymmetry in milliseconds.
• Risk Automation: Define the logic for warehousing risk internally versus hedging externally.
• Technical Translation: Convert mathematical strategies into scalable requirements for engineering teams.
• Risk Guardrails: Partner with the desk to define the engine’s operational boundaries and automated thresholds.
• Real-Time Leadership: Act as the technical anchor during high-leverage events, providing calibration and intervention when the system is under peak pressure.

Requirements:

• Quantitative Fluency: Deep understanding of probability and binary contracts; treating every event as a shifting probability curve.
• Pipeline Design: Experience building production-ready trading systems, from data ingestion to automated execution.
• Applied Data Science: Successful track record of deploying predictive models that learn from microstructure and price velocity.
• Systems Integrity: Expertise in building error-tolerant interfaces that remain stable under extreme throughput.