Associate Quantitative Researcher

About Torchcast AI

Torchcast AI is a Singapore-based company that builds AI systems to forecast real-world outcomes. Our platform combines forecasting-trained models, evidence retrieval, quantitative methods and probabilistic reasoning to help organisations make better decisions under uncertainty, across financial markets, economics, supply chains and technology.

The role

We are hiring Associate Quantitative Researchers for our Capital Markets team. You will find overlooked trading opportunities and turn research ideas into robust, executable systematic strategies. The work spans opportunity discovery, hypothesis design, data analysis, backtesting, execution and live performance review. Prior full-time trading experience is not required; relevant research, internships, competitions and independent projects will be considered.

What you will do

• Generate and prioritise hypotheses from market structure, price behaviour, cross-asset relationships, alternative data and changing market regimes.
• Translate hypotheses into systematic strategies with clear signals, portfolio construction, entry and exit logic, risk limits and capacity assumptions.
• Build reproducible datasets and backtests, controlling for leakage, overfitting, selection bias, transaction costs, slippage, latency and market impact.
• Use machine learning and AI-assisted workflows for signal discovery, forecasting, regime detection and research automation where they add measurable value.
• Define paper-trading and deployment criteria, monitor live behaviour and improve strategies based on evidence.
• Evaluate drawdowns, tail scenarios, concentration, liquidity, model instability and operational failure modes before and after launch.
• Present assumptions, results, limitations and trade-offs clearly to researchers and engineers.

Requirements

• Degree in a quantitative discipline such as mathematics, statistics, physics, computer science, engineering or financial engineering. A Master's or PhD is preferred; candidates with equivalent research or trading experience are welcome.
• Strong grounding in probability, statistics, linear algebra, time-series analysis, optimisation and experimental design.
• Strong Python skills and comfort with data and research code. SQL is useful; C++ or another performance-oriented language is a plus.
• Hands-on machine-learning experience is preferred, with an understanding of leakage, non-stationarity, explainability and model risk.
• Sound judgement, intellectual honesty, attention to detail and respect for risk controls and confidential information.
• Clear written and verbal communication.

How to apply

Apply through MyCareersFuture or email hiring@torchcast.ai with your CV and a short note on one trading opportunity you would like to research and why. Optional: a research note, code sample or track-record summary you are permitted to share (anonymise account details; do not send a current or former employer's proprietary information).

Torchcast AI is an equal opportunity employer. Selection is based on skills, experience and ability to do the job.