• Architected a multi-threaded Python options analytics platform with 6 concurrent threads, lock-based shared state, and clean separation of live execution and research workflows.

• Built end-to-end quant infrastructure: WebSocket streaming → real-time analysis → ML inference → signal generation → risk gating → Discord alerting → SQLite persistence → auto-retrain.

• Reduced debugging time with structured audit logs (JSONL per-decision tracing), replay scripts, and comprehensive test coverage across 435+ test cases.

• Implemented 14+ Discord webhook integrations with rate limiting (50 msg/min), strategy-specific routing, and error channel fallback for system monitoring.

What does it do?

• Real-time SPX 0DTE options trading system that streams live quotes via Charles Schwab WebSocket, computes gamma exposure walls, and generates credit spread signals every 60 seconds.

• Processes per-strike Greeks (delta, gamma, theta, vega, vanna, charm) across 240 option contracts to identify dealer hedging pressure zones and structural wall levels.

• Runs 4 ML models (RandomForest regime, XGBoost profitability filter, Hidden Markov regime, LSTM price predictor) plus 4 quantitative modules (GARCH(1,1), Bayesian Signal Scorer, Volume Regime Classifier, Move Exhaustion Tracker).

• Sends actionable trading alerts with strikes, targets, and stops to 14+ Discord channels covering 0DTE, monthly LEAPS, breakout, momentum, mean reversion, volatility, order flow, ORB, and wall-break strategies.

• 9-tab Streamlit dashboard for real-time monitoring of market state, option chain, signals, performance, risk/Greeks, flow intelligence, ML models, system health, and easy view for beginners.

• Persists per-minute greeks snapshots for reproducible backtesting with walk-forward validation, OOS holdouts, and temporal train/test splits (no look-ahead bias).

Team: Intelligent automation and RPA Admin

• Building AI Agent Testing Framework (LangSmith, LangChain, LangGraph)

• Administered and optimized 10+ AWS EC2-hosted Automation Anywhere RPA systems, ensuring high availability and seamless execution, resulting in significant operational efficiency gains.

• Engineered and deployed automation solutions within Salesforce to generate standardized reports and developed critical monitoring tools for Salesforce sandbox status, improving team data access.

• Contributed to the optimization of Salesforce data masking techniques, reducing processing time by 50% (from 6 hours to 3) and achieving measurable performance gains and system integrity.

Team: DevSecOps Engineering

• Developed and deployed a Java app on AWS-ECS, integrating Boomi API and AWS S3, reducing errors by 55% through proactive monitoring and notifications.

• Implemented a Splunk dashboard and alert system, using Machine Learning to detect outliers, improving error detection and response times.

• Designed and developed a monitoring service, from concept to deployment, resulting in a highly praised project that continues to assist the Boomi team.

Selected from a competitive applicant pool to be part of the Google x Basta GSWEP Program to work 1:1 with a Google Software Engineer solving technical problems.Selected from a competitive applicant pool to be part of the Google GSWEP Program to work 1:1 with a Google Software Engineer solving technical problems.

Team: Digital Experience Tracking

• Developed patent technology for voice-based automated testing using AI at American Express as part of the Digital Experience Tracking team.

• Led and implemented a Python-based automated testing system from scratch using Selenium and WebDriver, contributing 400+ lines of custom method functions.

• Deployed project locally and internally using Docker and Jenkins pipeline into internal cloud platform Hydra.