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.

Good to have skills:

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.

Quantitative Researcher