Junior Quantitative Researcher, Commodities and Cross Asset

Overview

In this role you will develop and test signals across commodity and cross-asset markets within a systematic investing framework. You’ll contribute across hypothesis generation, modelling, and implementation, with exposure to live strategy management and client-facing communication. You’ll work with portfolio managers and researchers to advance the firm’s research agenda and translate insights into scalable strategies. This is a research-heavy, collaborative role at a globally linked, multi-asset team that values rigor and investor outcomes.

Responsibilities

• Generate, research, and test signals across commodity and cross-asset markets
• Design and evaluate signals using rigorous statistical and quantitative methods
• Contribute to portfolio construction and risk analysis across the team’s strategies
• Monitor live performance and translate observations into new research hypotheses
• Produce client-facing content, including quarterly letters, white papers, blog posts, and webinars
• Support due diligence and consultant requests, where the research is subject to the highest level of scrutiny
• Collaborate with portfolio managers and researchers across Neuberger and contribute to the broader research agenda

Key requirements

• 3–5 years of relevant experience researching signals across commodity and cross-asset markets
• Strong proficiency in R or Python, with the ability to work with large financial datasets
• Solid grounding in statistical and mathematical modelling
• Understanding of portfolio construction, optimization, and risk analysis
• Comfort reading academic literature and translating it into testable ideas
• Fluent use of AI tools in research and coding, with verification discipline
• Familiarity with transaction costs is a plus
• Experience in systematic trading is a plus
• Strong academic record with a degree in a quantitative discipline; PhD or Master’s advantageous
• Intellectual curiosity and genuine interest in markets and forces that drive them
• Hands-on, rigorous approach from idea to implementation
• Excellent written and spoken English with ability to present to institutional clients
• Highly organized with ability to manage multiple research threads
• Collaborative and comfortable working with PMs, researchers, and clients

• intellectual curiosity
• strong communication
• collaboration
• R
• Python
• statistical modelling

…