Our client, a global regulated financial services group offering online trading across Forex, CFDs, commodities, indices, equities, and digital assets, is investing heavily in Artificial Intelligence and advanced analytics. We are seeking a Quant AI Specialist to apply quantitative research, machine learning, and AI techniques to complex trading, risk, and market analytics challenges in Dubai.
About the Role – Quantitative AI for Trading & Risk Analytics
Core Focus: Quantitative models for market behavior, liquidity patterns, and trading activity analysis
AI Applications: Forecasting, anomaly detection, client analytics, and market intelligence
Advanced Technologies: Large Language Models (LLMs), RAG, and AI-assisted analytics
Asset Classes: Forex, CFDs, commodities, indices, equities, and digital assets
Technical Stack: Python, Scikit-learn, XGBoost, TensorFlow, PyTorch, and SQL
Career Growth & Trading Intelligence Impact
Strategic Location: Dubai – a major global hub for regulated online trading and financial services
Deep Technical Application: Combine financial markets expertise with modern AI methodologies
Stakeholder Influence: Present research findings and model performance to senior management
Career Growth: Build specialized quant AI expertise at the intersection of trading and cutting-edge machine learning
Position Overview
This Quant AI Specialist role develops quantitative models to analyze market behavior, liquidity patterns, and trading activity, applying machine learning to forecasting, anomaly detection, and market intelligence use cases. You will develop AI-driven models for market prediction and behavioral analysis, evaluate and implement LLMs for research automation, develop quantitative frameworks for exposure monitoring and risk forecasting, support pricing and hedging optimization through advanced analytics, and collaborate with business and technology stakeholders to identify AI-driven innovation opportunities.
Why This Role Matters: As Quant AI Specialist, you apply cutting-edge machine learning and AI techniques to real trading, risk, and market analytics challenges across Forex, CFDs, and digital assets, combine deep quantitative modeling expertise with modern LLM and RAG technologies to drive research automation and decision support, develop predictive models for volatility forecasting and market regime detection that directly inform trading strategy, build statistical frameworks that detect unusual trading patterns and operational risks, and translate complex quantitative research into practical recommendations presented directly to senior management at a global regulated financial services group.
Key Responsibilities
Quantitative Research & Market Analytics
- Develop quantitative models to analyze market behavior, liquidity patterns, price movements, and trading activity
- Conduct research on market microstructure, execution quality, client behavior, and trading performance
- Design predictive models for volatility forecasting, market regime detection, and trading activity analysis
AI & Machine Learning Applications
- Apply machine learning algorithms to forecasting, anomaly detection, client analytics, and market intelligence
- Develop AI-driven models for market prediction, liquidity demand forecasting, and behavioral analysis
- Build statistical and machine learning frameworks to detect unusual trading patterns and operational risks
- Evaluate and implement Large Language Models (LLMs) and AI technologies for research automation
Risk & Performance Analysis
- Develop quantitative frameworks for exposure monitoring, profitability analysis, and risk forecasting
- Support pricing, execution, and hedging optimization through advanced analytics
- Produce actionable insights and recommendations based on quantitative research findings
Stakeholder Engagement
- Collaborate with business and technology stakeholders to identify AI-driven innovation opportunities
- Present research findings and model performance to senior management
- Translate complex quantitative concepts into practical business recommendations
Qualifications & Requirements
Educational Requirements
- Bachelor’s or Master’s degree in Quantitative Finance, Mathematics, Statistics, Data Science, Computer Science, Economics, or a related field
Experience Requirements
- 4-8 years of experience in quantitative analysis, trading analytics, financial data science, or quantitative research
- Experience within brokerage, FX, CFDs, crypto, institutional trading, market-making, or fintech is highly desirable
Technical Skills
- Advanced Python programming skills for quantitative analysis and machine learning
- Experience with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch
- Strong understanding of statistical modeling, time-series analysis, forecasting, and predictive analytics
- Experience working with financial market data, trading datasets, or large-scale transactional data
- Strong SQL and data analysis skills
- Familiarity with LLMs, Retrieval-Augmented Generation (RAG), and AI-assisted analytics
Essential Skills
- Strong understanding of financial markets, trading workflows, market structure, and risk management
- Excellent analytical, communication, and problem-solving skills
About This Opportunity
Our client is a global regulated financial services group with a strong presence across international markets, providing online trading and investment solutions across Forex, CFDs, commodities, indices, equities, and digital assets. The organisation is investing heavily in Artificial Intelligence, data transformation, automation, and advanced analytics to strengthen customer experience, operational performance, risk intelligence, and strategic decision-making.
Career Excellence: Apply cutting-edge AI and quantitative research to real trading and risk challenges at a global regulated financial services group in Dubai.
Who Should Apply?
- Quantitative Analysts: With 4-8 years in trading analytics or financial data science
- ML/AI Engineers in Finance: Skilled with Python, XGBoost, TensorFlow, or PyTorch
- FX/CFD Trading Researchers: Familiar with brokerage, market-making, or institutional trading
- LLM/RAG Specialists: Interested in applying generative AI to financial research automation
- Risk & Market Analytics Professionals: Comfortable presenting findings to senior management
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