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Trexquant

Quantitative trading via ML models

Head of Trading and Operations

Finance & BankingConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • A Bachelor's, Master's, or Ph.D. degree in Mathematics, Computer Science, or another related STEM field.
  • At least 8 years of experience in trading operations, middle office, or related functions at a quantitative hedge fund or systematic proprietary trading firm.
  • A strong understanding of global equity trading, trade lifecycle management, prime brokerage, clearing, and settlement.
  • Experience overseeing complex, automated trading environments across multiple markets and asset classes.
  • Strong technical skills, including a solid understanding of trading systems, data flows, and operational infrastructure.
  • The ability to anticipate issues, resolve them quickly, and implement practical solutions that improve operational efficiency.
  • Strong programming and systematic trading infrastructure fluency.
  • Strong organizational, leadership, and communication skills.
  • A hands-on, detail-oriented, and proactive approach, with a strong sense of ownership and accountability.

Responsibilities

  • Oversee daily trading activities across global markets and asset classes, ensuring accurate and timely execution, settlement, and reconciliation.
  • Ensure trading and operational processes function smoothly, proactively identifying and resolving issues before they affect the business.
  • Work closely with execution teams to monitor trading performance, transaction costs, broker connectivity, and execution quality.
  • Take ownership of ensuring that trading operations function reliably.

Desired Qualifications

  • Experience scaling trading operations across multiple asset classes.

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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