Quantitative Trader / Researcher – US Markets (HFT, Arbitrage, Derivatives, Fixed Income)

Quantitative Trader / Researcher – US Markets (HFT, Arbitrage, Derivatives, Fixed Income)

Shah Investors Home Ltd. , a SEBI-registered broking firm operating since 1994, is expanding its quantitative trading capabilities into US financial markets .

We are looking for a highly analytical Quantitative Trader / Researcher with minimum 2 years of experience in developing systematic trading strategies across US equities, derivatives, fixed income or cross-asset markets .

The role focuses on alpha generation, arbitrage opportunities, market microstructure and execution-efficient strategies , including exposure to HFT-oriented approaches . Candidates with a proven track record of strategy performance will be strongly preferred.

Key Responsibilities :

• Develop and implement systematic trading strategies in US markets
• Identify alpha signals and arbitrage opportunities using quantitative methods
• Build and evaluate backtests using risk-adjusted performance metrics such as Sharpe ratio and drawdown
• Analyze market microstructure, order flow and transaction costs
• Improve strategy robustness through continuous research and optimization

Required Skills

• Minimum 2 years experience in quantitative trading or research in US markets
• Strong understanding of systematic trading, arbitrage or HFT concepts
• Strong foundation in statistics, probability and quantitative methods
• Programming in Python (NumPy, Pandas, SciPy, scikit-learn)
• Experience working with financial time-series data

Preferred

• Experience with high-frequency or tick-level data
• Knowledge of options Greeks, volatility modelling or fixed income analytics
• Understanding of execution costs and slippage

Qualifications

• Master’s degree or higher in Mathematics, Statistics, Computer Science, Engineering, Finance, Physics or related quantitative field preferred
• Strong Bachelor’s candidates with relevant experience may also be considered

Important :

Preference will be given to candidates who can present validated research work, backtested or live strategy performance, or other measurable outcomes demonstrating practical capability.