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Quantitative Researcher

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Onsite

Quantitative Researcher

AAA Global

Quantitative Researcher

Skills

Deep LearningPythonMachine LearningAINLP / Natural Language ProcessingRisk Management

10 days ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

16 October 2026

What they need


Jr/Sr Quantitative Researcher | Systematic MFT | Tier 1 Hedge Fund

Team: Equities/Commodities/Futures/FX

Location: New York City or London

Experience: 3+ years

About the Opportunity

A leading global quantitative hedge fund is looking to hire a Quantitative Researcher primarily focused on systematic trading strategies.

The New York team develops and deploys systematic MFT strategies in equities and futures across global markets, leveraging large-scale datasets, statistical modeling, machine learning, and advanced quantitative techniques. Successful candidates will have the opportunity to collaborate and contribute across the full investment lifecycle, from idea generation and signal research through strategy development, validation, and implementation.

We are seeking outstanding quantitative researchers from leading academic and industry backgrounds to join our Systematic MFT teams. Candidates should have a proven ability to conduct rigorous research, develop predictive models, and translate data-driven insights into systematic trading strategies.

Responsibilities

  • Conduct independent quantitative research to identify, develop and evaluate systematic trading opportunities across global equities, commodities, futures and FX.
  • Develop, test and refine predictive alpha signals using large-scale financial, fundamental, alternative and unstructured datasets.
  • Apply statistical methods, machine learning, deep learning and other advanced quantitative techniques to uncover market inefficiencies and generate differentiated investment signals.
  • Research a range of systematic strategies, including statistical arbitrage, mean reversion, momentum, trend following and event-driven approaches.
  • Design and implement rigorous backtesting and validation frameworks to assess predictive power, statistical significance, robustness and out-of-sample performance.
  • Investigate improvements to existing signals and strategies, including portfolio construction, optimisation, position sizing, risk management and cross-signal integration.
  • Research signal monetisation, market impact, transaction costs and execution slippage to improve the conversion of predictive signals into realised trading performance.
  • Collaborate with quantitative researchers, portfolio managers and engineering teams to evaluate research findings, enhance existing strategies and translate successful research into production trading systems.

Candidate Profile

  • 3+ years of experience in quantitative research, systematic trading or a related quantitative investment role.
  • Master's or PhD in a quantitative discipline, such as mathematics, statistics, physics, computer science, engineering or a related field, from a strong academic institution.
  • Strong programming skills in Python and/or C++, with a solid understanding of algorithms, data structures and quantitative computing.
  • Strong research intuition and analytical ability, with a demonstrated capacity to identify predictive signals, distinguish signal from noise and evaluate model robustness.
  • Experience working with large-scale datasets, financial time series, statistical modelling or machine learning techniques.
  • Intellectual curiosity, independent problem-solving skills, high research standards and the ability to thrive in a collaborative, performance-driven environment.

Preferred Experience

  • Experience researching and developing medium-frequency systematic trading strategies, particularly those with intraday holding period or approximately 2–5 trading days.
  • Demonstrated experience generating, validating or deploying alpha signals across equities, futures, commodities, FX or other liquid markets.
  • Specialisation in one or more relevant research areas, including statistical arbitrage, machine learning/AI alpha, NLP and alternative data, quantamental research, portfolio construction and optimisation, or signal monetisation and execution.
  • Experience with cross-sectional modelling, predictive financial models, financial time-series analysis, feature engineering or robust backtesting methodologies.
  • A track record of translating research into measurable improvements in strategy performance, live trading results or portfolio P&L.
  • Background at a leading quantitative hedge fund, systematic asset manager, proprietary trading firm or similarly rigorous research environment.

Please email a copy of your CV to [email protected] if you are interested in this opportunity.

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