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Junior Quantitative Researcher, Commodities and Cross Asset

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: LGBT Great
Full Time position
Listed on 2026-09-05
Job specializations:
  • Finance & Banking
    Financial Analyst, Data Scientist, Capital Markets, Portfolio & Asset Management
Salary/Wage Range or Industry Benchmark: 85000 - 140000 GBP Yearly GBP 85000.00 140000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

About Neuberger:

Neuberger was founded in 1939 to do one thing: deliver compelling investment results for our clients over the long term. This remains our singular purpose today, driven by a culture rooted in deep fundamental research, the pursuit of investment insight and continuous innovation on behalf of clients, and facilitated by the free exchange of ideas across the organization.

As a private, independent, employee-owned investment manager, Neuberger is structurally aligned with the long‑term interests of our clients. We have no external parent or public shareholders to serve, nor other lines of business to distract us from our core mission, and with our employees and their families invested alongside our clients - plus 100% of employee deferred cash compensation directly linked to team and firm strategies - we are truly in this together.

From offices in 40 cities worldwide, Neuberger manages a range of equity, fixed income, private equity and hedge fund strategies on behalf of institutions, advisors and individual investors worldwide. With more than 700 investment professionals and more than 2,900 employees in total, Neuberger has built a diverse team of individuals united in their commitment to client outcomes and investment excellence. Our culture has afforded us enviable retention rates among our senior investment staff and has earned us citations in the top‑ranked firms (among those with 1,000 or more employees) in the Pensions & Investments “Best Places to Work in Money Management” survey each year since 2013.

For more information, please visit our website at

Position Overview:

Established in 2008, our team is dedicated to delivering innovative, active, broad‑based commodity investing and also manages a global multi‑asset risk parity portfolio. Based in New York and London, we apply an academically grounded approach to systematic investing across a diversified set of investment channels. The mission of this role is to develop signals and portfolio construction methods across commodity and cross‑asset markets and to translate that work into insights for clients.

In this role, you will conduct original research across commodity and cross‑asset markets, systematizing fundamental insight into signals that inform live portfolios. You will contribute across the full research lifecycle, from hypothesis generation and statistical modelling through implementation and ongoing performance analysis, while gaining direct exposure to live strategy management and client engagement.

Primary 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 /

Qualifications:
  • 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 comfortably with large financial datasets.
  • Solid grounding in statistical and mathematical modelling, with the judgment to choose the right tool for the problem at hand.
  • 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, combined with the discipline to verify outputs.
  • Familiarity with transaction costs and their impact on signal design is a plus.
  • Experience in systematic trading is a plus.
  • Strong academic record with a degree in a quantitative discipline, such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Economics, from a leading university; a PhD or Master’s is advantageous.
  • Intellectual curiosity and a genuine…
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