Python Quant Developer - Backtesting & Research Engine
Iām building a research-grade analytical trading system and am looking for an experienced Python/quant developer to continue development of an existing backtesting & research platform.
The project already exists and includes:
- Data loading layer (database + APIs)
- Streamlit-based web interface
- Core backtesting logic (partially implemented)
- YAML-based strategy configuration (recently added)
The goal is to evolve this into a robust research platform focused on:
- Correct methodology
- Realistic execution modeling
- Clean, modular architecture
This is not a one-off task. Iām looking for a long-term collaborator who can gradually take ownership of the technical side.
Scope of Work (current and planned):
Backtesting Core
- Declarative strategy definitions (config-driven, YAML/JSON)
- Entry/exit rules using AND / OR logic over indicators
- Single instruments, batch backtesting, and later spreads / pairs
Execution Model
- Configurable execution delay (N bars after signal)
- Market, stop, limit, stop-limit orders
- Commissions, slippage, explicit execution assumptions
Indicators
- External indicator registry
- Dynamic indicator computation
- Adding new indicators without touching core engine
Optimization & Validation
- Parameter optimization (Optuna or similar)
- In-sample/out-of-sample testing
- Walk-forward analysis
Risk & Analysis
- Drawdown, stability metrics
- Monte Carlo on trade sequences
Web Interface
- Strategy builder UI (not only YAML files)
- Ability to configure strategies via web forms
- Visual analytics of results
Important (context):
The project already has a working codebase and Docker setup. The developer is expected to:
- Review existing architecture
- Fix and improve current implementation
- Extend features gradually
- Help shape the final system design
Requirements
- Strong Python (pandas, numpy)
- Experience with backtesting / trading systems
- Understanding of look-ahead bias, OOS validation, overfitting
- Ability to work with an existing codebase
Nice to have
- Experience with Streamlit
- Quant/research background
- Prior work on trading platforms
Apply tot his job
Apply To this Job
The project already exists and includes:
- Data loading layer (database + APIs)
- Streamlit-based web interface
- Core backtesting logic (partially implemented)
- YAML-based strategy configuration (recently added)
The goal is to evolve this into a robust research platform focused on:
- Correct methodology
- Realistic execution modeling
- Clean, modular architecture
This is not a one-off task. Iām looking for a long-term collaborator who can gradually take ownership of the technical side.
Scope of Work (current and planned):
Backtesting Core
- Declarative strategy definitions (config-driven, YAML/JSON)
- Entry/exit rules using AND / OR logic over indicators
- Single instruments, batch backtesting, and later spreads / pairs
Execution Model
- Configurable execution delay (N bars after signal)
- Market, stop, limit, stop-limit orders
- Commissions, slippage, explicit execution assumptions
Indicators
- External indicator registry
- Dynamic indicator computation
- Adding new indicators without touching core engine
Optimization & Validation
- Parameter optimization (Optuna or similar)
- In-sample/out-of-sample testing
- Walk-forward analysis
Risk & Analysis
- Drawdown, stability metrics
- Monte Carlo on trade sequences
Web Interface
- Strategy builder UI (not only YAML files)
- Ability to configure strategies via web forms
- Visual analytics of results
Important (context):
The project already has a working codebase and Docker setup. The developer is expected to:
- Review existing architecture
- Fix and improve current implementation
- Extend features gradually
- Help shape the final system design
Requirements
- Strong Python (pandas, numpy)
- Experience with backtesting / trading systems
- Understanding of look-ahead bias, OOS validation, overfitting
- Ability to work with an existing codebase
Nice to have
- Experience with Streamlit
- Quant/research background
- Prior work on trading platforms
Apply tot his job
Apply To this Job