I design and build systems at the intersection of cloud infrastructure and quantitative trading. On the cloud side, I architect AWS solutions and lead engineering teams. On the trading side, I build algorithmic scanners, sentiment engines, and conviction-scoring tools — all powered by Python, ThinkScript, and AI.
- Languages: Python (Primary), ThinkScript (ThinkorSwim)
- Frameworks: Streamlit, React, Node.js
- Cloud: AWS (RDS, Lambda, S3, CloudWatch)
- Data & AI: PRAW (Reddit API), Pandas, yfinance, Generative AI (MCP)
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Stock Buddy Insights — AI-powered stock analysis platform built with React and Supabase. Combines fundamental scoring, sentiment analysis, and technical signals into a single conviction dashboard.
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ThinkorSwim Studies & Scanners — Production-grade ThinkScript library including the Institutional Accumulation Scanner, Fallen Angels Scanner, Elite Fundamentals Scanner, and TTM Squeeze Pro study. Used in a live trading workflow.
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reddit_praw — Python-based Reddit scraper designed for stock sentiment analysis and social signal extraction using the PRAW API.
- Streamlit-based mobile web app for automated stock conviction scoring
- Generative AI protocols (MCP) to enhance financial research workflows
- Expanding ThinkScript scanner library with ORB and Snapback mean-reversion setups
I approach the market systematically — using scanners to surface high-probability setups, not gut feel. My edge is at the intersection of fundamental quality (Elite Fundamentals), technical timing (TTM Squeeze, ORB), and institutional activity (volume flow, VWAP, MFI). All scans run on the S&P 500 universe with a primary trading window of 8:30–10:30 AM CT.
- LinkedIn: linkedin.com/in/raneliahu
- Medium: @Eliahu.ran
- GitHub: github.com/Eliahur7