Senior Quantitative Researcher — Multi-Asset Cta

THE ROLE Own the research, development and iteration of systematic multi-asset strategies across a global instrument universe spanning CME, ICE, LME, EUREX, SGX, JPX and ASX. Work across the full strategy spectrum: trend following, time-series and cross-sectional momentum, carry, term structure and volatility. Build portfolios under real-world constraints — multi-currency exposure, multiple time zones and trading calendars: risk budgeting, volatility targeting, FX exposure treatment and execution timing across sessions. Form a view on where strategies should and should not be exposed, informed by the global macro environment: central bank policy cycles, inflation paths, geopolitical risk and cross-market flows. Monitor live performance, run attribution, detect decay and recalibrate. REQUIREMENTS Experience 5+ years of quantitative research experience at an international hedge fund or global asset manager, including at least 3 years in CTA or multi-asset systematic strategies. Backgrounds we particularly value: dedicated CTA managers (AHL, Winton, Aspect, Transtrend, Campbell, Graham and similar), multi-strategy platforms (Millennium, Balyasny, ExodusPoint, Schonfeld and similar), and systematic macro funds. Strategies you researched must have traded live. You should be able to describe how long they ran, how far live results diverged from backtest, and why. Research coverage must include non-domestic markets, and span more than a single exchange or asset class. You have been through at least one full cycle of strategy decay and repair — and can explain what you concluded at the time, what you changed, and why. Global Market Knowledge Familiarity with contract design, liquidity profiles, delivery and roll mechanics across the major global futures markets, and how these differ by venue. Understanding of the structural differences between markets: central-bank expectations pricing in developed rates futures, session-dependent liquidity in Asia-Pacific, industrial and inventory dynamics in commodities. Practical grasp of multi-currency portfolios: decomposing returns between local and base currency, the cost of FX hedging, and the relationship between carry and rate differentials. Ability to connect macro cycles to strategy performance in a testable way, rather than as post-hoc narrative. Research Skills Master's degree or above in mathematics, statistics, physics, computer science, financial engineering or a related quantitative field. Strong Python (pandas, numpy, scipy); able to run the full pipeline independently from data handling through backtesting to portfolio optimisation. Solid statistical and time-series foundations: stationarity, cointegration, panel regression, bootstrap methods, multiple-testing correction. Professional scepticism toward backtest results, with an instinct for spotting data snooping, survivorship bias, look-ahead bias and parameter overfitting. Grounding in portfolio construction: risk parity, covariance shrinkage, convex optimisation. Quantitative understanding of transaction costs, market impact and cross-market capacity, informed by live trading rather than theory alone. Other English as a working language — able to read primary research literature and exchange rulebooks, and to deal directly with offshore brokers and data vendors. Able to close the loop independently: idea → validation → deployment → iteration. Currently working in Singapore, or willing to relocate. Employment Pass sponsorship available. PREFERRED Experience with strategies that carried USD 100m equivalent or more in live capital. Background in cross-asset macro or options volatility research. Experience with Asia-Pacific session instruments or cross-border relative value. Experience building a multi-factor risk model in-house. Chinese and English bilingual ability, for coverage of onshore commodity markets.