Quant AI Specialist

Company Overview

Role Overview

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.