Quant AI Specialist
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Key skills for this role
About the Role
Boundless is seeking a Quant AI Specialist for a global regulated financial services group in Dubai. The role applies quantitative research, machine learning, and AI to solve trading, risk management, and market analytics challenges.
Key Skills for This Role
Responsibilities
- 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
- Identify opportunities to improve trading performance through data driven insights and quantitative techniques
- Apply machine learning algorithms to forecasting, anomaly detection, client analytics, and market intelligence use cases
- 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 and decision support
- 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
- Collaborate with business and technology stakeholders to identify opportunities for AI driven innovation
Requirements
- Advanced Python programming skills for quantitative analysis and machine learning
- Experience with machine learning 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
- Experience with data visualization and reporting tools
- Bachelor's or Master's degree in Quantitative Finance, Mathematics, Statistics, Data Science, Computer Science, Economics, or related field
- 4–8 years of experience in quantitative analysis, trading analytics, financial data science, or quantitative research
- Strong understanding of financial markets, trading workflows, market structure, and risk management
- Experience within brokerage, FX, CFDs, crypto, institutional trading, market making, or fintech environments is highly desirable
- Excellent analytical, communication, and problem solving skills
Full Job Posting
Company Overview
- Our client, a global regulated financial services group with a strong presence across international markets, provides 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.
Role Overview
- We are seeking a Quant AI Specialist to apply quantitative research, machine learning, and artificial intelligence techniques to solve complex trading, risk management, pricing, and market analytics challenges.
- The successful candidate will combine expertise in financial markets with modern AI methodologies to develop predictive models, trading intelligence solutions, and advanced analytics that support business decision making.
- This role requires a deep understanding of market dynamics, quantitative modeling, and the practical application of AI within electronic trading environments.
Key Responsibilities
- 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.
- Identify opportunities to improve trading performance through data driven insights and quantitative techniques.
- Apply machine learning algorithms to forecasting, anomaly detection, client analytics, and market intelligence use cases.
- 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 and decision support.
- 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.
- Collaborate with business and technology stakeholders to identify opportunities for AI driven innovation.
Technical Requirements
- Advanced Python programming skills for quantitative analysis and machine learning.
- Experience with machine learning 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.
- Experience with data visualization and reporting tools.
Qualifications
- Bachelor's or Master's degree in Quantitative Finance, Mathematics, Statistics, Data Science, Computer Science, Economics, or a related field.
- 4–8 years of experience in quantitative analysis, trading analytics, financial data science, or quantitative research.
- Strong understanding of financial markets, trading workflows, market structure, and risk management.
- Experience within brokerage, FX, CFDs, crypto, institutional trading, market making, or fintech environments is highly desirable.
- Excellent analytical, communication, and problem solving skills.
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