Quantitative Researcher
K-Hawk Capital · Not specified · onsite · Posted 1d ago
About a minute. You'll make an account on the way through.
About this role
Quantitative Researcher – Futures & ETF Market Making
Overview
K-Hawk Capital is a systematic trading firm focused on high-turnover intraday strategies in equities, ETFs, and futures. Our performance depends on sophisticated quantitative models, disciplined transaction-cost control, deep market microstructure insight, and tight integration with live trading systems.
We are hiring an experienced **Quantitative Researcher specializing in Futures and ETF Market Making** to research, develop, and continuously improve our market-making strategies, with a focus on optimal control, inventory management, market microstructure alpha, and execution optimization.
Key Responsibilities
- Design, implement, and optimize systematic market-making strategies across liquid futures and ETFs.
- Develop optimal control frameworks for dynamic quoting, inventory management, position sizing, and risk management.
- Research and implement short-horizon market microstructure alpha signals using order flow, order-book imbalance, trade activity, and liquidity dynamics.
- Build and calibrate models for fill probability, queue position, adverse selection, and short-term price movements.
- Develop inventory-aware quoting strategies that dynamically adjust bid/ask prices, spreads, and order sizes based on market conditions.
- Research stochastic control, dynamic programming, and reinforcement learning approaches to market making.
- Model limit order book dynamics, including order arrivals, cancellations, queue depletion, and liquidity regimes.
- Develop and optimize execution algorithms to maximize spread capture while minimizing adverse selection, market impact, and transaction costs.
- Research cross-asset relationships between equity index futures and ETFs to improve pricing, hedging, and market-making decisions.
- Build and evaluate realistic backtesting and simulation frameworks incorporating queue priority, latency, partial fills, and exchange matching rules.
- Analyze historical and live trading data to identify performance leakage, improve execution quality, and increase strategy capacity.
- Monitor production trading strategies and continuously refine quoting, inventory management, and execution logic.
Required Qualifications
- 5+ years of experience in quantitative research, electronic market making, or systematic trading.
- Hands-on experience developing or optimizing market-making strategies in futures and/or ETFs.
- Strong understanding of optimal control, stochastic processes, inventory management, and quantitative optimization.
- Deep knowledge of market microstructure, limit order books, order flow dynamics, and adverse selection.
- Proven experience developing short-horizon predictive signals and market microstructure alpha.
- Experience with transaction cost modeling, fill probability estimation, and execution optimization.
- Proficiency in Python and experience working with high-frequency market data.
- Experience using Claude AI or similar AI coding assistants to accelerate research, prototyping, development, testing, and documentation.
- Excellent analytical, quantitative, and problem-solving skills.
- Bachelor's, Master's, or PhD in a STEM field (Mathematics, Physics, Engineering, Computer Science, Statistics, or related discipline).
Preferred Qualifications
- Experience market making CME equity index futures (ES, NQ, RTY) and liquid ETFs (SPY, QQQ, IWM, DIA).
- Experience applying reinforcement learning, stochastic optimal control, or dynamic programming to market-making problems.
- Experience with L2/L3 market data, market-by-order feeds, and queue-aware execution simulations.
- Familiarity with low-latency trading systems and exchange connectivity.
- Strong C++ programming skills.
- - Demonstrated success improving market-making profitability, Sharpe ratios, execution quality, or strategy capacity.
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