As a Quant Strategist / Researcher at Shah Investors Home Ltd., you will play a crucial role in designing, researching, and developing systematic trading strategies across equity and derivatives markets. Your responsibilities will include:
Researching and developing systematic trading strategies across equity and derivatives markets. - Building quantitative models using statistical and machine learning techniques. - Performing backtesting and analyzing performance metrics (Sharpe, drawdown, risk-adjusted returns). - Implementing and optimizing strategies using Python. - Analyzing financial time-series data and applying market regime models to identify alpha signals and inefficiencies. - Monitoring live strategies and continuously improving models by researching new signals, factors, and market opportunities. To excel in this role, you should possess the following skills:
Strong understanding of financial markets, derivatives, and systematic trading. - Robust foundation in statistics, probability, and quantitative methods. - Proficiency in Python programming (Pandas, NumPy, SciPy, scikit-learn). - Experience in quantitative research, backtesting, and data analysis. - Strong analytical and problem-solving mindset. Preferred skills include knowledge of machine learning techniques applied to trading, options Greeks, volatility modeling, experience with large or high-frequency datasets, and understanding of portfolio optimization or execution concepts. Qualifications required for this position include a Bachelors or Masters degree in Finance, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, along with 14 years of experience in quantitative research, algorithmic trading, or financial data analysis. At Shah Investors Home Ltd., we value curiosity about markets, a research-driven mindset, the ability to test ideas rigorously using data, and a passion for systematic trading and quantitative modeling. The compensation for this position includes a competitive salary with performance-based incentives depending on experience and strategy contribution. As a Quant Strategist / Researcher at Shah Investors Home Ltd., you will play a crucial role in designing, researching, and developing systematic trading strategies across equity and derivatives markets. Your responsibilities will include:
Researching and developing systematic trading strategies across equity and derivatives markets. - Building quantitative models using statistical and machine learning techniques. - Performing backtesting and analyzing performance metrics (Sharpe, drawdown, risk-adjusted returns). - Implementing and optimizing strategies using Python. - Analyzing financial time-series data and applying market regime models to identify alpha signals and inefficiencies. - Monitoring live strategies and continuously improving models by researching new signals, factors, and market opportunities. To excel in this role, you should possess the following skills:
Strong understanding of financial markets, derivatives, and systematic trading. - Robust foundation in statistics, probability, and quantitative methods. - Proficiency in Python programming (Pandas, NumPy, SciPy, scikit-learn). - Experience in quantitative research, backtesting, and data analysis. - Strong analytical and problem-solving mindset. Preferred skills include knowledge of machine learning techniques applied to trading, options Greeks, volatility modeling, experience with large or high-frequency datasets, and understanding of portfolio optimization or execution concepts. Qualifications required for this position include a Bachelors or Masters degree in Finance, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, along with 14 years of experience in quantitative research, algorithmic trading, or financial data analysis. At Shah Investors Home Ltd., we value curiosity about markets, a research-driven mindset, the ability to test ideas rigorously using data, and a passion for systematic trading and quantitative modeling. The compensation for this position includes a competitive salary with performance-based incentives depending on experience and strategy contribution.