About the role
AI summarisedThis role is for a quantitative trading strategist focused on developing and refining trading signals for crude and refined products markets. The position involves applying statistical modeling, machine learning, and quantitative research to uncover predictive patterns and support trading decisions. The individual will collaborate with traders, build backtesting frameworks, and contribute to systematic analytics initiatives within a global trading organization based in Singapore.
UtilitiesOnsiteTrading
Key Responsibilities
- Generate and research strategies for crude and products markets using statistical methods, machine learning, feature engineering and quantitative modelling
- Work closely with traders to translate market intuition into testable hypotheses, validate signal behaviour and improve decision making across short term and medium term horizons
- Analyse large volumes of market, fundamental and alternative data to identify patterns, anomalies and structural behaviours relevant to Crude & Products trading
- Build and maintain robust back testing frameworks, evaluate strategy performance, stress test signals and ensure statistical validity across regimes
- Develop scalable research tooling and systematic strategy components using Python and modern data science libraries
- Contribute signal and modelling insight to broader systematic and data driven initiatives across the trading organization
- Monitor live strategy behaviour, support execution logic improvements, and partner with developers to deploy production ready analytics
Requirements
- Strong quantitative background (MSc/PhD preferred) in applied math, statistics, econometrics, data science, computer science or similar fields
- Expertise in statistical modelling, machine learning, predictive analytics, feature engineering and time series methods applied to financial or commodity markets
- Advanced Python skills for research, modelling and data processing; experience with ML libraries (scikit learn, PyTorch, TensorFlow) is a plus
- Ability to analyse large datasets, uncover signal patterns and communicate findings clearly to traders and commercial teams
- Experience building and validating back tests, including performance attribution, robustness checks and sensitivity analysis
- Curiosity about market structure, pattern discovery and quantitative alpha generation in commodity futures and spreads
- A proactive, research driven mindset with strong documentation habits and attention to statistical integrity