Principal Quant

Job description

**What You’ll Do** 1. **Quantitative Strategies Design and Implementation** - Devise and own a **highly consistent, coherent, and principled quantitative strategy** across trading, market-making, and alpha generation. - Ensure that individual trading algorithms, market-making models, and execution parameters fit together into a **harmonious system** designed for global efficiency. - Own the **end-to-end correctness, backtesting, and live performance** of quantitative strategies in production. - Take ownership over **minimizing adverse selection**, managing slippage, and optimizing execution quality under stress scenarios. - Act as the **primary quantitative expert** for evaluating market behavior and strategy outcomes: - analyzing realized volatility versus model predictions - diagnosing strategy performance drift and optimizing alpha signals - driving model adjustments based on market-making effectiveness and P&L - Treat live trading results as the ultimate validation of design, continuously refining strategies based on real-world market dynamics. Biasing towards **statistical robustness** and long-term scalability. 2. **Quantitative Product Ownership** - Devise and own a **highly consistent, coherent, and principled quantitative direction** across trading, margining, liquidation, lending, and risk-related products. - Ensure that individual models, parameters, and mechanisms fit together into a **harmonious system**, rather than a collection of locally-correct but globally-fragile designs. - Own the **end-to-end correctness, feasibility, and desirability** of quantitative products in production. - Take ownership over **preventing tricky edge cases**, stress scenarios, and failure modes from hitting production. - Act as the **first line of defense** for user, partner, and internal feedback related to quantitative behavior: - answering questions about correctness and intent - diagnosing whether feedback reflects misunderstanding, edge cases, or real design flaws - driving fixes or adjustments when models do not behave as intended - Treat post-launch behavior as a continuation of product design, continuously refining models based on observed outcomes and feedback. Biasing strongly towards **system consistency during revisions**, and avoiding repeated fragile patches. 3. **Cross-Functional Leadership & Execution** - Act as the **technical lead** for the research pipelines and infrastructure required to scale GRVT’s trading capabilities. - Write **exceptionally optimized and clean code (Python/C++)** for backtesting, research tools, and execution modules. - Collaborate with engineering to bridge the gap between research and high-performance production systems: - designing low-latency data pipelines for strategy inputs - optimizing the execution engine for market-making responsiveness - building automated monitoring and attribution tools - Take direct responsibility for **validating implementations** of quantitative products: - design and execute deep testing in non-production and production environments - reason about edge cases, stress scenarios, and failure modes that others are unlikely to catch - use QA support where helpful, but remain **personally accountable** for correctness - Own the outcome when quantitative products are mis-implemented, even if gaps were not caught by QA, recognizing that the domain complexity requires quant-level validation. ### **Risk Management & Live Trading** - Take **full P&L responsibility** for live trading strategies and systemic risk behavior in production. - Act as a key responder during incidents involving: - abnormal trading behavior - liquidation anomalies - margin, risk, or insurance fund issues - extreme market conditions or tail events - Be accountable for **real-time risk monitoring** during market volatility, including: - diagnosing root causes under pressure - advising on mitigations, parameter changes, or temporary safeguards - balancing user impact, platform safety, and long-term risk - Lead or co-lead post-incident analysis for quantitative failures, ensuring: - root causes are correctly understood (model vs implementation vs assumption) - durable fixes are made to models, parameters, or system design - learnings are fed back into product design and operational playbooks - Proactively identify latent systemic risks and work with engineering and risk teams to reduce them **before** they manifest as incidents. - Design trading strategies with real-time operability in mind, including: - observability of key metrics and invariants - explainability of system behavior during abnormal events - safe failure modes and bounded blast radius **What We’re Looking For (Core Requirements)** We’re looking for **exceptional senior ICs** who combine strong product leadership with deep quantitative skill. You should demonstrate: - Prior experience building or operating **trading venues, exchanges, or market infrastructure**. - A strong background in **quant**, with hands-on experience in quantitative trading, or market-making - Proven strength as a **Product Manager**, including: - owning outcomes end-to-end - driving cross-functional alignment - writing high-quality, precise specifications - Deep understanding of margining, liquidation, leverage, and systemic risk mechanics. - Strong operational mindset and comfort owning live P&L in production. - Excellent communication skills, especially when explaining complex quantitative reasoning clearly. - Sound judgment under ambiguity and high-stakes decision-making.