Quantitative Analyst

Our client is a global financial trading firm using AI-powered quantitative research to support advanced trading strategies across FX and CFD markets. Focused on innovation and performance, the firm is expanding its quantitative analytics team to enhance its research and predictive modeling capabilities.

They are currently seeking a Quantitative Analyst (AI, FX & CFDs) to develop and refine machine learning models that inform trading strategies, risk assessments, and market behavior analysis.

Job Overview

We are seeking a highly analytical and detail-oriented Quantitative Analyst with strong experience in data modeling, AI techniques, and financial market research. The ideal candidate will support the development of algorithmic trading strategies by building predictive models, analyzing large datasets, and identifying actionable insights within FX and CFD markets.

This role is ideal for someone who enjoys exploring data patterns, building robust forecasting tools, and collaborating closely with quant traders and developers to improve model accuracy and trading logic.

Key Responsibilities

1. Quantitative Research & Model Development
   Conduct research to identify market patterns, pricing inefficiencies, and alpha signals using statistical and machine learning models.
   Develop forecasting models using deep learning, supervised learning, and time-series analysis to support trading strategies.
   Analyze market microstructure, volatility trends, and macroeconomic data to enhance signal quality and model robustness.

1. Data Analysis & Signal Generation
   Work with high-frequency and historical FX/CFD datasets to discover predictive relationships.
   Build and validate features that drive machine learning models, improving signal-to-noise ratios and model interpretability.
   Collaborate on developing alternative data pipelines, such as sentiment analysis, macro indicators, and order book data.

1. Backtesting & Performance Evaluation
   Design and conduct backtesting experiments to validate model performance under historical market conditions.
   Evaluate model stability, overfitting risk, and out-of-sample robustness using statistical techniques.
   Present findings and recommendations to the trading team for strategy refinement and implementation.

1. Cross-Functional Collaboration
   Work with quant traders and developers to translate research insights into production-ready components.
   Support continuous model refinement based on live market performance and new data inputs.
   Contribute to internal research libraries, documentation, and knowledge-sharing initiatives.

Qualifications & Skills

• 3-5 years of experience in quantitative research, data science, or analytics within financial markets (FX/CFDs preferred).
• Strong proficiency in Python, with experience in pandas, NumPy, scikit-learn, and ML libraries such as TensorFlow or PyTorch.
• Solid understanding of statistical modeling, machine learning, and time-series analysis.
• Experience working with large datasets, data preprocessing, and feature engineering.
• Familiarity with backtesting tools and market data APIs.
• A quantitative degree (Math, Stats, Physics, Computer Science, Financial Engineering) is preferred.