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Quantitative Researcher

Quantitative Researcher

k-hawk capital
5-7 Years
Not Disclosed
  • Posted 11 hours ago
  • Be among the first 10 applicants

Job Description

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.

More Info

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Key Skills

order flow dynamics

execution optimization

high-frequency market data

quantitative optimization

limit order books

market-making strategies

transaction cost modeling

low-latency trading systems

Claude AI

L2 L3 market data

queue-aware execution simulations

fill probability estimation

About Company

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