Senior Quant Researcher

Skills: Python Alpha research in the Indian equity and options markets. Role Overview We are seeking a Senior Quantitative Researcher to lead alpha research initiatives in Indian equity and derivatives markets. The role focuses on ideation, modeling, and deployment of systematic trading strategies, with a strong emphasis on turning research into production-ready trading systems. You will play a key role in shaping our research agenda, mentoring junior researchers, and contributing directly to strategy PnL. Responsibilities Alpha & Strategy Research Design, develop, and evaluate systematic trading strategies across equities, index derivatives, and volatility products. Conduct deep-dive research into market microstructure, behavioral inefficiencies, and risk premia. Translate research insights into production-grade signals, algo systems and and portfolios Build and maintain robust statistical and ML models for forecasting returns, volatility, and liquidity. Implement risk modeling techniques including regime detection, factor decomposition, and stress testing. Technology & Engineering Architect and enhance research infrastructure for large-scale data mining and experimentation. Ability to write production level engineering code to ensure efficient deployment and monitoring of strategies. Maintain high standards of code quality, reproducibility, and documentation. Preferred Skills & Experience 4+ years of experience in quantitative research and systematic trading. Strong programming skills in Python with an emphasis on numerical computing, data analysis, and research tooling. Demonstrated ability to apply statistical inference, hypothesis testing, and experimental design in financial research. Proven track record of developing profitable or production-ready strategies with rigorous backtesting and validation practices. Deep understanding of derivatives, market microstructure, probability theory, and statistical modeling. Experience with machine learning, time-series econometrics, and optimization techniques for portfolio construction or signal extraction. Strong intuition for data, ability to work with noisy datasets, and familiarity with techniques to avoid overfitting and lookahead bias. Ability to independently drive research from idea to validation to deployment. Strong communication skills and ability to articulate complex quantitative ideas clearly. Completed Bachelors degree in a quantitative subject such as Computer Science, Applied Mathematics, Statistics, or related field. Compensation Competitive Base Salary in accordance with the experience. Performance Bonus linked to strategy PnL Candidates with portable or existing algorithmic strategies (live or well-validated) will have a significant advantage and may be eligible for enhanced compensation structures. Position is not a remote only position. Some flexibility around remote work is possible, but it will require in-person presence.