The project
B2H is building a Sharia-compliant trading assistant: a financial analysis platform that surfaces investment opportunities and explains every recommendation it makes.
The system combines technical analysis (support and resistance, Japanese candlesticks, indicators), machine learning models, risk management and Islamic finance rules. It produces BUY / HOLD / AVOID signals with an explanation attached — and never executes an order automatically. The decision stays human.
You join a team of three interns — AI, Machine Learning, Software — to build an MVP in one month.
Your mission
Design the platform's decision engine and its explainable recommendation system.
This is the role that answers the question the product's credibility rests on: why does the system recommend this asset?
Responsibilities
- Design the decision framework combining market analysis, ML predictions, risk evaluation and Sharia rules
- Develop the recommendation algorithms that generate investment signals
- Implement confidence scoring mechanisms
- Build explainable AI features that surface the reasons behind a recommendation
- Analyse feature importance and model decision factors
- Develop the Sharia compliance rule engine assessing asset eligibility
- Implement filtering of non-compliant assets
Technologies
Python · SHAP · explainable AI techniques · rule-based systems
Deliverables
- AI recommendation engine
- Explainable AI module
- Sharia compliance verification system
- Technical documentation
Who we are looking for
- Studying computer science, data science, artificial intelligence or equivalent
- Solid Python; first exposure to machine learning is a plus
- An appetite for decision systems and model interpretability
- Intellectual rigour: in finance, a recommendation you cannot justify is worthless
- An interest in Islamic finance is welcome — not required, we will bring you up to speed
Timeline
A one-month internship in four stages: framing and research, core development, integration with the other components, then testing, evaluation and the final MVP presentation.
How to apply
Fill in the form below with your CV. We reply within 48 business hours.