About the Role
We are a start-up proprietary trading firm building a high-performance quantitative research capability in Bangalore. We are looking for a rigorous, intellectually curious Quantitative Analyst to join our systematic trading research team.
In this role, you will develop, backtest, and refine quantitative trading models across digital asset and alternative markets. You will work with large-scale market datasets (on-chain, order book, derivatives), apply statistical and machine learning methods to identify alpha signals, and collaborate closely with discretionary traders and engineers to bring strategies from research to production.
This is not a support role — you will own the full lifecycle from hypothesis generation through model validation to live performance monitoring.
If you think in distributions, not predictions, and want to build systematic strategies in a market where inefficiencies are abundant but fleeting, this is the role.
Key Responsibilities
Design, develop, and backtest systematic trading strategies using statistical, econometric,



and machine learning techniques across digital asset spot, derivatives, and DeFi markets.
Identify and extract alpha signals from diverse data sources: order book dynamics, on-chain metrics, funding rates, liquidation cascades, sentiment data, and macro indicators.
Build and maintain robust backtesting frameworks with proper handling of transaction costs, slippage, market impact, and survivorship/look-ahead bias.
Develop market regime classification models to dynamically adjust strategy parameters and risk exposure.
Conduct research on market microstructure, cross-exchange arbitrage opportunities, basis trading, and volatility surface dynamics in Digital assets derivatives.
Collaborate with engineers to productionise validated models — define signal generation pipelines, feature engineering specifications, and real-time inference requirements.
Monitor live strategy performance, investigate P&L; attribution and

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