Python Options Algo Development
Budget: ₹75,000 – ₹150,000 INR
**Python Intraday Options System Development (NIFTY / SENSEX)**
I’m starting a fresh build of a **modular intraday options trading system** for Indian indices (**NIFTY / SENSEX**) and I’m looking for a **Python engineer** who can take this from zero to a **stable Phase 1 MVP**.
### Phase 1 scope
This is a green-field build. The initial milestone should cover:
* Robust market-data and option-chain ingestion via the **Upstox API**
* A **rule-based signal engine** that can be extended later for **AI-assisted analytics modules**
* **Dynamic stop-loss / take-profit logic** that adapts to live market conditions
* **Paper-trading execution** with position tracking (**no live orders in Phase 1**)
* Structured logging for post-trade analysis, debugging, and future extensions
### Tech expectations
Core stack should be **Python 3.x**. You may recommend tools/frameworks such as **FastAPI, asyncio, pandas**, or other practical choices that keep the code modular, maintainable, and responsive for intraday use.
A clean separation between:
* **data ingestion**
* **signal logic**
* **risk / execution**
* **logging / storage**
is important, because later phases may include:
* AI-assisted analytics
* pre-market news/context bias
* confidence scoring
* post-trade analysis
* end-of-day reporting
### What I’d like to see from you
Please share:
* relevant **GitHub repos / past projects / code samples**
* prior experience with **broker APIs, trading systems, data pipelines, or analytics workflows**
* a brief outline of how you would architect Phase 1
* estimated timeline and budget for this phase
### Acceptance criteria for Phase 1
1. End-to-end **paper trade cycle** can run unattended from market open to close.
2. Signals and paper fills are stored with timestamps, prices, and relevant metadata in a queryable store (**CSV, SQLite, or your recommended DB**).
3. Codebase is **modular, reproducib**
I’m starting a fresh build of a **modular intraday options trading system** for Indian indices (**NIFTY / SENSEX**) and I’m looking for a **Python engineer** who can take this from zero to a **stable Phase 1 MVP**.
### Phase 1 scope
This is a green-field build. The initial milestone should cover:
* Robust market-data and option-chain ingestion via the **Upstox API**
* A **rule-based signal engine** that can be extended later for **AI-assisted analytics modules**
* **Dynamic stop-loss / take-profit logic** that adapts to live market conditions
* **Paper-trading execution** with position tracking (**no live orders in Phase 1**)
* Structured logging for post-trade analysis, debugging, and future extensions
### Tech expectations
Core stack should be **Python 3.x**. You may recommend tools/frameworks such as **FastAPI, asyncio, pandas**, or other practical choices that keep the code modular, maintainable, and responsive for intraday use.
A clean separation between:
* **data ingestion**
* **signal logic**
* **risk / execution**
* **logging / storage**
is important, because later phases may include:
* AI-assisted analytics
* pre-market news/context bias
* confidence scoring
* post-trade analysis
* end-of-day reporting
### What I’d like to see from you
Please share:
* relevant **GitHub repos / past projects / code samples**
* prior experience with **broker APIs, trading systems, data pipelines, or analytics workflows**
* a brief outline of how you would architect Phase 1
* estimated timeline and budget for this phase
### Acceptance criteria for Phase 1
1. End-to-end **paper trade cycle** can run unattended from market open to close.
2. Signals and paper fills are stored with timestamps, prices, and relevant metadata in a queryable store (**CSV, SQLite, or your recommended DB**).
3. Codebase is **modular, reproducib**