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Trexquant

Quantitative trading via ML models

Head of Systematic Macro Strategy Team

Quantitative ResearchConfirmed live in the last 24 hours
Full-timeUnited States

About the Job

Requirements

  • Bachelor's, Master's, or Ph.D. degree in Mathematics, Statistical Modeling, Computer Science, or another related STEM field.
  • At least 5 years of experience researching and trading systematic macro-based strategies.
  • Experience managing or leading a team of quantitative researchers.
  • Strong quantitative skills.
  • Proficiency in Python.

Responsibilities

  • Build and lead the Systematic Macro Strategy team, driving the development, enhancement, and ongoing monitoring of macro alpha signals to support scalable and sustainable performance.
  • Design, develop, and scale a diversified suite of systematic macro strategies across asset classes, ensuring robustness from research through production.
  • Collaborate closely with the execution team to optimize strategy implementation, align macro strategies with existing portfolios, and improve overall trading efficiency.
  • Identify, source, and integrate high-quality datasets for macro research; develop and maintain data pipelines to support efficient backtesting and live trading.
  • Partner with the development team to enhance platform capabilities, improving the accuracy, speed, and reliability of simulation and execution for macro strategies.
  • Work with the risk team to define, monitor, and manage macro-specific risk exposures while optimizing capital allocation across strategies.
  • Communicate research insights and strategy performance to senior management, ensuring alignment between quantitative macro initiatives and broader investment objectives.

About the Company

Trexquant

Quantitative trading via ML models

Trexquant is a quantitative finance firm that builds multi-asset portfolios using machine learning. It develops investment and research tools that ingest a wide range of data variables to create complex trading models and strategies, which in turn generate trading signals. These signals guide decisions across global markets. The product works by applying advanced machine learning to large datasets to create predictive models and rule-based strategies, which drive portfolio construction and trading actions through the firm’s platform. Trexquant differentiates itself by emphasizing the breadth of data it uses and the depth of machine-learning driven models to craft multi-asset portfolios, aiming to produce signals that outperform global market conditions. The company’s goal is to generate investment performance that beats benchmarks by using data-driven signals and diversified, multi-asset strategies.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Stamford, CT
Founded
2012

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