Quantitative Strategy Developer
7 days ago
Are you a coder who understands
alpha
?
Not indicators. Not chart patterns.
Real, statistical
edge
.
At
QFI Capital
, we are scaling our Algorithmic Trading Desk across Nifty, BankNifty, and Equity FnO—building proprietary systems driven by probability, statistics, and high-performance computing.
We are
NOT
looking for beginners.
The Role:
You will not just be writing code; you will be engineering edge. You will work directly with the founders to design, backtest, and deploy automated trading strategies that can survive slippage, transaction costs, and market noise.
What You Will Do:
- Strategy Development: Design and code Mean Reversion, Statistical Arbitrage, and Momentum strategies based on quantitative data (not just simple EMA crosses).
- Rigorous Backtesting: Build backtesting engines that account for real-world friction (slippage, latency, liquidity).
- Execution Algorithms: Optimize order placement logic to minimize market impact.
- Data Analysis: Work with tick-level data to find recurring inefficiencies in Indian Indices.
Who We Are Looking For (The "Non-Negotiables"):
- Proven Track Record: You must have a portfolio of strategies that have generated returns in Live Markets. Paper trading results are not enough.
- Quant Proficiency: Strong grasp of time-series analysis, volatility modeling, and risk management (Sharpe/Sortino ratios, Drawdown control).
Technical Stack:
- Python: Expert level (Pandas, NumPy, SciPy, VectorBT, Backtrader).
- APIs: Experience with Indian Broker APIs (Zerodha Kite, Interactive Brokers, Shoonya, etc.).
- Database: Handling large historical datasets (SQL/NoSQL).
- Market Knowledge: Deep understanding of Indian Options Greeks, Implied Volatility, and Expiry day dynamics.
Why Join Us?
- Direct Impact: You aren't a cog in a machine. Your code will directly drive the firm's P&L..
- Innovation: We are building a proprietary tech stack, giving you the freedom to innovate without legacy code constraints.
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