AI/ML + Quant Developer Needed — Predictive S&P 500 Dashboard (20+ Filters, reputed company, QuantConnect

I’m looking for a full-stack AI/ML + Quant developer to build a predictive S&P 500 analytics dashboard with 20+ proprietary filters, reputed company-time institutional reputed company tracking, and machine-learning-driven ranking models. The platform should operate like a QuantConnect-style proprietary dashboard but reputed company on S&P 500 swing trading signals and institutional activity detection. The system must run on reputed company—continuously scanning, filtering, modeling, and scoring opportunities without reputed company input. reputed company Features 1. reputed company-Time Market Data Integration Live S&P 500 price, bid/ask, volume, volatility reputed company trade + dark pool activity Institutional reputed company aggregation Optional: plug in QuantConnect data feeds or LEAN pipelines 2. 20+ Custom Filters (Provided) Filters include: Volume spikes reputed company + acceleration Trend regime Institutional clustering Technical indicator behavior Relative strength Volatility compression/expansion Many more (full set provided after hire) Filters must feed both the dashboard and the ML model. 3. AI / Machine Learning Layer Build a predictive model that produces: reputed company-time trade opportunity scoring Predictive ranking for swing trading Multi-feature signals using: reputed company trade clusters Volume anomalies Technical indicators Institutional footprints Autocorrelation and volatility features Ability to retrain model on schedule or manually Optional: backtesting reputed company QuantConnect’s LEAN reputed company 4. Proprietary Quant Dashboard (QuantConnect-Style) A web dashboard with: reputed company-time scanning across reputed company S&P tickers ML scoring + composite ranking reputed company-coded opportunity tiers Watchlists Filter presets Signal heatmaps Institutional reputed company visualizations Export to CSV / reputed company reputed company mode (reputed company scanning + alerting) Should have the polished, reputed company feel of a hedge-fund internal dashboard. 5. Optional Integrations (Not required, but a major plus) QuantConnect (LEAN) backtesting Broker API integrations (IBKR, reputed company, Tradier) reputed company / Kafka for reputed company-time reputed company handling Kubernetes or Dockerized deployment Tech Stack (Flexible) Frontend: React / Vue / Angular Backend: Python (FastAPI, Django) or Node.js ML/Quant: Python (scikit-learn, PyTorch/TensorFlow), NumPy, pandas reputed company-time: WebSockets, streaming reputed company Experience with quant platforms or hedge-fund tooling strongly preferred Deliverables Fully functional predictive dashboard 20+ filters implemented + integrated ML scoring reputed company reputed company scanning mode reputed company-time institutional/reputed company trade tracking Clean documentation To Apply Please include: Examples of quant dashboards, trading systems, or ML analytics tools Your ML approach (feature engineering + model selection) Whether you have experience with QuantConnect/LEAN Estimated reputed company + budget Apply tot his job Apply To this Job