Quant AI Specialist

Boundless; Dubai; On-site; AED 500,000 - 700,000; Full time

Job summary

Boundless is 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 and advanced analytics that support business decision-making.

The role requires deep understanding of market dynamics, quantitative modeling, and the

Qualifications

• Bachelor's or Master's in a quantitative field.
• 4–8 years of experience in quantitative analysis or trading analytics.
• Strong knowledge of financial markets, market structure and risk management.
• Experience in brokerage, FX, CFDs, crypto, or fintech environments is desirable.
• Excellent analytical, communication, and problem-solving skills.

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 ML 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 ML frameworks to detect unusual trading patterns and operational risks.
• Evaluate and implement 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 AI-driven opportunities.
• Present research findings and model performance to senior management.
• Translate complex quantitative concepts into practical business recommendations.

Skills

Python

ML frameworks

Time-series analysis

SQL

LLMs

Data visualization

Education

Bachelor's or Master's degree in Quantitative Finance, Mathematics, Statistics, Data Science, Computer Science, Economics, or related field

Tools

Scikit-learn

XGBoost

TensorFlow/PyTorch

Pandas/Numpy

SQL tooling

Job description

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

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.
• Identify opportunities to improve trading performance through data-driven insights and quantitative techniques.

AI & Machine Learning Applications

• 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.

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 opportunities for AI-driven innovation.
• Present research findings and model performance to senior management.
• Translate complex quantitative concepts into practical business recommendations.

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.