Quant Strategist / Researcher (Algorithmic Trading)
About Shah Investors & Role :
Shah Investors Home Ltd. is a SEBI-registered broking firm operating since 1994, known for its trust, integrity and long-standing presence in financial markets.
We welcome highly skilled and ambitious individuals who are passionate about their work and interested in contributing to a research-driven environment across quantitative research, trading systems, data science, and financial modeling.
Currently We are looking for a highly analytical Quant Strategist / Researcher who can design, research and develop systematic trading strategies across equity and derivatives markets. The ideal candidate combines skills from quantitative research, trading and programming to convert market ideas into robust algorithmic models.
This role offers strong career growth for individuals passionate about financial markets and data-driven research. You will gain exposure to Indian and global markets, working on strategy development and quantitative models across multiple market structures and trading environments.
Key Responsibilities :
- Research and develop systematic trading strategies across equity and derivatives markets.
- Build quantitative models using statistical and machine learning techniques.
- Perform backtesting and analyze performance metrics (Sharpe, drawdown, risk-adjusted returns).
- Implement and optimize strategies using Python.
- Analyze financial time-series data and apply market regime models to identify alpha signals and inefficiencies.
- Monitor live strategies and continuously improve models by researching new signals, factors, and market opportunities.
Required Skills :
- Strong understanding of financial markets, derivatives and systematic trading.
- Strong foundation in statistics, probability and quantitative methods.
- Python programming (Pandas, Num Py, Sci Py, scikit-learn).
- Experience in quantitative research, backtesting, and data analysis.
- Strong analytical and problem-solving mindset.
Preferred Skills :
- Machine learning techniques applied to trading.
- Knowledge of options Greeks and volatility modelling.
- Experience with large or high-frequency datasets.
- Understanding of portfolio optimization or execution concepts.
Qualifications :
- Bachelor’s or Master’s degree in Finance, Mathematics, Statistics, Computer Science, Engineering or related quantitative field.
- 1–4 years of experience in quantitative research, algorithmic trading, or financial data analysis.
What We Value :
- Curiosity about markets and a research-driven mindset.
- Ability to test ideas rigorously using data rather than intuition alone.
- Passion for systematic trading and quantitative modelling.
Compensation :
