Contact person: Business Client

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Location: Ajax, Canada

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a solid, cost-conscious build of an AI-powered bot that can trade equities intraday. The core focus is the stock market and the workflow must suit a fast, day-trading rhythm: high-frequency data intake, rapid signal generation, robust tight risk management limits, and immediate order routing.

You and I will work side-by-side—from refining the logic through live deployment—so clean, well-commented code and open communication matter as much as performance. I am comfortable iterating in Python and expect the usual stack around NumPy, pandas, scikit-learn or TensorFlow/PyTorch, plus broker APIs such as Interactive Brokers or Alpaca. If you prefer another stable API, let’s discuss it early.

Although stocks are the first milestone, I’d like the architecture to be modular enough to plug into Binance later, so separating data adapters from the strategy layer is important.

Deliverables
• End-to-end trading script or package ready for live stock day trading
• Back-testing module using historical intraday data with clear P&L, Sharpe, drawdown metrics
• Real-time dashboard or CLI showing open positions, exposure, and key statistics
• Minimalistic risk-management rules (max position size, hard stop, daily loss cap) baked in
• Setup guide so I can redeploy on a low-cost VPS or local machine

Acceptance criteria
The bot must execute at least a week of paper trading without manual intervention, stay within the risk limits we define together, and generate a reproducible trade log that matches the back-test logic. Once that milestone is met we will schedule the cut-over to live capital.

If this sounds like a build you can own, tell me how you would structure the project and the tech you’d lean on first." (client-provided description)