Contact person: AI Trading Integration With Sentiment

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Location: Hyderabad, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I have an existing rules-based trading strategy and I now want it to react automatically to fresh information pulled from the market. The scope covers both stocks and crypto. Your task is to build a clean pipeline that feeds my strategy with:

• Historical price series gathered through public endpoints such as Alpha Vantage, Yahoo Finance API and IEX Cloud (use all that are needed for depth and redundancy).
• Live headlines and tick-by-tick news from Bloomberg, Reuters and Yahoo Finance, plus the broker feeds offered by Dhan, Upstox and Angel One.
• Social-media chatter if it adds meaningful signal.

With that data in hand, apply modern NLP techniques and an LLM-based classifier to score market sentiment, then expose those scores so that my strategy can consume them in real-time and on replayed historical runs. I expect Python code (pandas, asyncio, transformers, LangChain or similar—your call), clear documentation, and the option to switch individual sources on or off from a config file.

Deliverables will be accepted when:
1. A script (or micro-service) reliably downloads, cleans and stores historical OHLCV for any symbol I request.
2. Another service streams live news and broker updates with sub-second latency.
3. Sentiment scores come back in JSON or through a REST/gRPC call and are reproducible on historical back-fills.
4. A short notebook or script shows my strategy reacting to the new sentiment feature on both stocks and crypto.

If you have shipped comparable algo-trading or NLP projects before, please mention them—code samples or architecture diagrams are welcome." (client-provided description)