Quant Developer Required – Semi-Automated Indian Equity Trading System

## Quant Developer Required – Semi-Automated Indian Equity Trading System We are seeking an experienced quantitative developer to build and validate a semi-automated trading system for NSE equities. The objective is to create a disciplined system that identifies trading opportunities, evaluates them using quantitative and AI-assisted checks, calculates risk and presents the final trades for human approval. ### Initial Scope * Develop and validate one intraday strategy and one swing-trading strategy. * Define clear entry, exit, stop-loss and position-sizing rules. * Backtest the strategies using reliable Indian market data. * Include realistic brokerage, STT, GST, exchange charges and slippage. * Conduct out-of-sample and walk-forward testing. * Build a scanner that provides: * Stock and strategy name * Entry level * Stop-loss and target * Risk-reward ratio * Suggested position size * Reason for selection * Conditions that would invalidate the trade * Create a simple dashboard or Telegram-based interface. * Enable paper trading and maintain complete signal and trade logs. * Integrate with FYERS or another suitable broker API after successful validation. ### AI-Assisted Review Layer The system should include an AI-assisted validation step before a signal is presented to the trader. The review should consider: * Overall market trend * Sector strength * Price and volume behaviour * Liquidity and volatility * Risk-reward quality * Event or news risk * Conflicting technical signals Each opportunity should be classified as: * Qualified * Watchlist * Rejected The system must provide a brief reason for the classification. AI should support decision-making and must not independently execute trades. ### Risk Controls * Maximum risk per trade * Maximum daily loss * Maximum open positions * Maximum sector exposure * Duplicate-order protection * Stale-data and API-failure protection * Emergency stop or kill switch ### Required Deliverables * Strategy-rules document * Python source code * Data and backtesting module * Backtesting and validation report * Signal scanner * AI-assisted review module * Dashboard or Telegram interface * Paper-trading module * Risk-management controls * Installation and operating guide * Source-code handover and demonstration ### Project Stages **Stage 1:** Strategy definition and architecture **Stage 2:** Backtesting and independent validation **Stage 3:** Scanner, AI review and dashboard **Stage 4:** Paper trading and performance review **Stage 5:** Optional broker integration after approval Payment will be milestone-based. Progression to each stage will depend on satisfactory completion and validation of the previous stage. ### Applicant Requirements Applicants must demonstrate experience in: * Quantitative strategy development * Python-based trading systems * Indian equity markets * Backtesting without look-ahead bias or data leakage * Walk-forward and out-of-sample validation * Broker API integration * Trading risk-management systems Please include: * Relevant previous projects * Sample backtesting reports or dashboard screenshots * Your proposed approach * Recommended data and broker API * Milestone-wise quotation * Confirmation of complete source-code ownership and handover Generic applications or guaranteed-return claims will not be considered.