Quantitative Developer for Market Structure Engine
Budget: $10 – $30 USD
PROJECT TITLE SIMPLE PROJECT $20 MAX
Python Quantitative Trading Developer Needed – Custom Non-Print Market Structure Engine, LineBreak Reconstruction, AI Integration
PROJECT OVERVIEW
I am looking for an experienced Python developer with strong knowledge of market data processing, algorithmic trading systems, event-driven architecture, and custom chart construction.
This is NOT a traditional trading bot project.
The objective is to build a proprietary market structure research and analysis platform using Interactive Brokers Time & Sales data as the primary input.
The system will be used for future AI-driven analysis and strategy development.
REQUIRED SKILLS
* Python
* Interactive Brokers API (IBKR)
* Real-time market data processing
* Time & Sales processing
* PostgreSQL / TimescaleDB
* WebSocket architecture
* Custom chart construction
* Multithreading / asynchronous programming
* Trading system development
* Historical replay systems
* Quantitative research tools
Experience with the following is highly preferred:
* Market microstructure
* Footprint concepts
* Order flow analysis
* Liquidity modeling
* AI integration
* LLM integration
* Machine learning pipelines
PROJECT OBJECTIVE
The system will receive live Time & Sales data from Interactive Brokers.
From that data, the program will build two completely separate structural datasets:
1. BID NON-PRINT DATA ENGINE
Track only Bid-side non-print events.
Examples:
* Zero-print bid levels
* Non-traded bid levels
* Bid liquidity voids
* Bid structural gaps
* Bid persistence measurements
2. ASK NON-PRINT DATA ENGINE
Track only Ask-side non-print events.
Examples:
* Zero-print ask levels
* Non-traded ask levels
* Ask liquidity voids
* Ask structural gaps
* Ask persistence measurements
These two data engines must remain completely independent.
The purpose is to model liquidity absence rather than traditional price movement.
CUSTOM LINEBREAK ENGINE REQUIREMENTS
The system must construct proprietary Line Break charts from the Non-Print datasets.
This is a critical requirement.
The Line Break charts are NOT visual indicators.
They are data structures.
The Line Break construction must be accurate because all downstream classification depends on these chart states.
Required:
100 Bid Non-Print Line Break charts
100 Ask Non-Print Line Break charts
Resolutions:
1 Line Break through 100 Line Break
Total:
200 independent Line Break data engines
IMPORTANT
I do NOT require 200 rendered chart windows.
I specifically do NOT want visual rendering of 200 charts because of CPU and memory overhead.
The charts should exist internally as data structures only.
The system should maintain and update them in memory and/or database form.
CLASSIFICATION ENGINE
I already have the classification logic and prompts.
The programmer does NOT need to invent classification formulas.
The system will apply provided formulas to each Line Break engine.
Each chart will maintain multiple classification scores.
Examples:
* Compression Score
* Expansion Score
* Dominance Score
* Synchronization Score
* Structural State Score
The exact formulas and rules will be provided.
DATA STORAGE REQUIREMENTS
Store:
* Raw Time & Sales
* Bid Non-Print events
* Ask Non-Print events
* Structural classifications
* Historical states
* Line Break states
* Replay data
Database:
Preferred:
* PostgreSQL
* TimescaleDB
Alternative recommendations are welcome.
DASHBOARD REQUIREMENTS
The system should provide a single primary dashboard.
The dashboard should contain:
MAIN TRADING WINDOW
One visual chart only.
This chart will be used for:
* Future strategy development
* Historical replay
* Backtesting
* Trade simulation
* Signal visualization
This is the only full chart that requires rendering.
STRUCTURAL STATUS PANELS
Display:
100 Bid Structural Panels
100 Ask Structural Panels
Total:
200 small status blocks
These are NOT charts.
These are lightweight dashboard elements.
Each block should display the current classification state and scores for its corresponding Line Break engine.
Examples:
* Compression
* Expansion
* Transition
* Strength
* Synchronization
Simple color coding and numerical values are sufficient.
AI INTEGRATION
The platform is being designed to support future local AI integration.
The architecture should be designed so future agents can consume:
* Historical data
* Classification data
* Structural states
* Synchronization data
Preferred output options:
* JSON
* WebSocket
* API endpoints
PERFORMANCE REQUIREMENTS
This project is intended to run continuously.
Efficiency is important.
The architecture should:
* Minimize CPU usage
* Minimize memory usage
* Support real-time updates
* Support historical replay
* Support future AI integration
DELIVERABLES
* Fully documented Python code
* Installation instructions
* Database schema
* Real-time data ingestion
* Bid Non-Print Engine
* Ask Non-Print Engine
* 200 internal Line Break engines
* Classification framework integration
* Dashboard UI
* Historical replay capability
* Source code ownership transferred upon completion
WHEN APPLYING
Please include:
1. Examples of trading systems you have built.
2. Experience with Interactive Brokers API.
3. Experience with custom chart construction.
4. Experience with event-driven market data systems.
5. Experience with databases used for tick data.
6. Estimated timeline.
7. Estimated cost.
Please do not apply if your experience is limited to simple indicator scripting or retail trading bots.
This project requires strong software engineering and market data architecture experience.
Python Quantitative Trading Developer Needed – Custom Non-Print Market Structure Engine, LineBreak Reconstruction, AI Integration
PROJECT OVERVIEW
I am looking for an experienced Python developer with strong knowledge of market data processing, algorithmic trading systems, event-driven architecture, and custom chart construction.
This is NOT a traditional trading bot project.
The objective is to build a proprietary market structure research and analysis platform using Interactive Brokers Time & Sales data as the primary input.
The system will be used for future AI-driven analysis and strategy development.
REQUIRED SKILLS
* Python
* Interactive Brokers API (IBKR)
* Real-time market data processing
* Time & Sales processing
* PostgreSQL / TimescaleDB
* WebSocket architecture
* Custom chart construction
* Multithreading / asynchronous programming
* Trading system development
* Historical replay systems
* Quantitative research tools
Experience with the following is highly preferred:
* Market microstructure
* Footprint concepts
* Order flow analysis
* Liquidity modeling
* AI integration
* LLM integration
* Machine learning pipelines
PROJECT OBJECTIVE
The system will receive live Time & Sales data from Interactive Brokers.
From that data, the program will build two completely separate structural datasets:
1. BID NON-PRINT DATA ENGINE
Track only Bid-side non-print events.
Examples:
* Zero-print bid levels
* Non-traded bid levels
* Bid liquidity voids
* Bid structural gaps
* Bid persistence measurements
2. ASK NON-PRINT DATA ENGINE
Track only Ask-side non-print events.
Examples:
* Zero-print ask levels
* Non-traded ask levels
* Ask liquidity voids
* Ask structural gaps
* Ask persistence measurements
These two data engines must remain completely independent.
The purpose is to model liquidity absence rather than traditional price movement.
CUSTOM LINEBREAK ENGINE REQUIREMENTS
The system must construct proprietary Line Break charts from the Non-Print datasets.
This is a critical requirement.
The Line Break charts are NOT visual indicators.
They are data structures.
The Line Break construction must be accurate because all downstream classification depends on these chart states.
Required:
100 Bid Non-Print Line Break charts
100 Ask Non-Print Line Break charts
Resolutions:
1 Line Break through 100 Line Break
Total:
200 independent Line Break data engines
IMPORTANT
I do NOT require 200 rendered chart windows.
I specifically do NOT want visual rendering of 200 charts because of CPU and memory overhead.
The charts should exist internally as data structures only.
The system should maintain and update them in memory and/or database form.
CLASSIFICATION ENGINE
I already have the classification logic and prompts.
The programmer does NOT need to invent classification formulas.
The system will apply provided formulas to each Line Break engine.
Each chart will maintain multiple classification scores.
Examples:
* Compression Score
* Expansion Score
* Dominance Score
* Synchronization Score
* Structural State Score
The exact formulas and rules will be provided.
DATA STORAGE REQUIREMENTS
Store:
* Raw Time & Sales
* Bid Non-Print events
* Ask Non-Print events
* Structural classifications
* Historical states
* Line Break states
* Replay data
Database:
Preferred:
* PostgreSQL
* TimescaleDB
Alternative recommendations are welcome.
DASHBOARD REQUIREMENTS
The system should provide a single primary dashboard.
The dashboard should contain:
MAIN TRADING WINDOW
One visual chart only.
This chart will be used for:
* Future strategy development
* Historical replay
* Backtesting
* Trade simulation
* Signal visualization
This is the only full chart that requires rendering.
STRUCTURAL STATUS PANELS
Display:
100 Bid Structural Panels
100 Ask Structural Panels
Total:
200 small status blocks
These are NOT charts.
These are lightweight dashboard elements.
Each block should display the current classification state and scores for its corresponding Line Break engine.
Examples:
* Compression
* Expansion
* Transition
* Strength
* Synchronization
Simple color coding and numerical values are sufficient.
AI INTEGRATION
The platform is being designed to support future local AI integration.
The architecture should be designed so future agents can consume:
* Historical data
* Classification data
* Structural states
* Synchronization data
Preferred output options:
* JSON
* WebSocket
* API endpoints
PERFORMANCE REQUIREMENTS
This project is intended to run continuously.
Efficiency is important.
The architecture should:
* Minimize CPU usage
* Minimize memory usage
* Support real-time updates
* Support historical replay
* Support future AI integration
DELIVERABLES
* Fully documented Python code
* Installation instructions
* Database schema
* Real-time data ingestion
* Bid Non-Print Engine
* Ask Non-Print Engine
* 200 internal Line Break engines
* Classification framework integration
* Dashboard UI
* Historical replay capability
* Source code ownership transferred upon completion
WHEN APPLYING
Please include:
1. Examples of trading systems you have built.
2. Experience with Interactive Brokers API.
3. Experience with custom chart construction.
4. Experience with event-driven market data systems.
5. Experience with databases used for tick data.
6. Estimated timeline.
7. Estimated cost.
Please do not apply if your experience is limited to simple indicator scripting or retail trading bots.
This project requires strong software engineering and market data architecture experience.