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Trexquant

Quantitative trading via ML models

Quantitative Researcher - Execution

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A Bachelor's, Master's, or Ph.D. degree in Mathematics, Statistical Modeling, Computer Science, or another related STEM field.
  • At least 3 years of experience working in an electronic execution role within a quantitative trading company.
  • Strong quantitative skills, attention to detail, and proficiency in Python programming.

Responsibilities

  • Optimize daily execution of multi-billion notionals across equities, futures, and an expanding list of asset classes.
  • Develop tools to continuously analyze execution data across various trading instruments.
  • Manage and update trading cost and market impact models across all asset classes.
  • Extract actionable insights from recent execution performance and years of historical data.
  • Develop hypotheses and design studies to further improve trading, and present results to senior researchers.
  • Work with brokers to implement new execution strategies to improve transaction costs and fill rates.
  • Work with the Operations team to ensure brokers provide best execution services.

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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