We're looking for a Quant Researcher to research, design, and validate systematic trading strategies across Indian equities, indices, commodities, and derivatives. You'll work with large-scale market and alternative datasets to uncover predictive signals, develop quantitative models, and improve trading performance through rigorous research and analysis.
What You'll Do
- Research and develop systematic trading strategies using historical market and tick-level data.
- Design and conduct robust backtests to evaluate strategy performance.
- Analyse order book and market microstructure data to identify trading opportunities.
- Explore alternative datasets to discover new alpha signals.
- Apply statistical, econometric, and machine learning techniques to generate and validate trading ideas.
- Evaluate strategy performance using risk-adjusted metrics and recommend improvements.
- Perform exploratory data analysis and hypothesis testing to uncover market inefficiencies.
- Collaborate with traders and quantitative developers to translate research into actionable strategies.
What You'll Need
- Strong programming skills in Python or any other language.
- Experience working with tick data, order book data, and historical market datasets.
- Hands-on experience with quantitative research and strategy back testing.
- Solid understanding of probability, statistics, time-series analysis, and machine learning.
- Knowledge of Indian equity, futures, options, and commodity markets, including market microstructure.
- 1–5 years of experience in quantitative research, algorithmic trading, or systematic investing.
Nice to Have
- Experience with alternative data research.
- Familiarity with feature engineering and alpha factor research.
- Knowledge of derivatives pricing and volatility modeling.
- Experience using cloud computing or distributed computing for large-scale research.
- Publications, Kaggle achievements, or open-source contributions related to quantitative finance or machine learning.
