Devansh D.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

Quant Developer specializing in algorithmic trading systems, broker API integration, low-latency execution infrastructure, and backtesting platforms across equities, options, futures, commodities, and crypto. I build production-ready trading software for live execution, paper trading, multi-account management, portfolio monitoring, risk management, MTM controls, alerts, analytics, and web-based trading platforms using Python, real-time market data, and cloud infrastructure. My experience covers end-to-end trading technology, from market data feed capture, signal generation, and strategy logic to broker connectivity, order routing, execution monitoring, reporting, and dashboard systems. I work on fully automated trading systems, semi-automated execution workflows, paper trading environments, scanner-based platforms, advanced trading dashboards, multi-account systems, and large broker-connected trading products built for real market use. I can build and integrate around brokers, APIs, and platforms such as Interactive Brokers (IBKR)/ TWS/ IB Gateway, Alpaca, Charles Schwab, MT5 / MetaTrader 5, TradingView webhooks, Binance, Zerodha, Kite Connect, Angel One SmartAPI, XTS API, Polygon, REST APIs, WebSockets, and custom execution bridges. My systems commonly include multi-account handling, copy trading workflows, percentage-based position sizing, capital allocation logic, order management systems, stop-loss and take-profit rules, kill switches, max loss controls, MTM-based risk management, portfolio-level controls, position reconciliation, and execution tracking. On the strategy side, I work with workflows related to momentum, mean reversion, breakout, Open Range Breakout (ORB), trend-following, reversal strategies, options strategies, straddles, spreads, volatility-based systems, scalping, intraday trading, swing trading, candle formations, candlestick pattern analysis, RSI, Bollinger Bands, EMA-based strategies, ATR-based risk logic, support and resistance models, divergence logic, and scanner-driven strategy automation. I also build custom backtesting engines, optimization frameworks, signal dashboards, and paper trading systems to help move from research to live deployment. My core stack includes Python, pandas, NumPy, asyncio, FastAPI, Flask, Streamlit, PySide6 / Qt, Plotly, Dash, SQLAlchemy, PostgreSQL, SQLite, Redis, requests, aiohttp, ib_insync, ccxt, backtrader, vectorbt, TA-Lib, scikit-learn, Docker, Linux, and AWS services such as EC2 and S3, along with deployment workflows for web-based platforms, dashboards, internal tools, and real-time monitoring systems. I can also build communication and monitoring layers with Telegram alerts, Discord alerts, WhatsApp alerts, chat-based workflows, and notification systems. In addition to core trading infrastructure, I can support GPT and Claude-based real-time stock and market analysis, AI-assisted signal interpretation, reporting workflows, and decision-support tools for trading operations. This is useful for traders, firms, and teams that want intelligence layers alongside execution and monitoring systems. I focus on building software that is structured, scalable, execution-aware, and usable in real trading environments. Whether you need a broker-connected execution engine, a low-latency trading system, a multi-account automation platform, a futures or options trading dashboard, a crypto trading system, a paper trading setup, a backtesting framework, or a complete web-based trading product, I can help design and build it end to end.