Quantitative Researcher: ML Models for Alpha Signals

SIG Susquehanna

Pennsylvania

Presencial

USD 85 000 - 120 000

Tempo integral

14 dias+

Uma candidatura completa num minuto

Currículo e carta de apresentação personalizados, prontos a enviar.

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Resumo da oferta

SIG Susquehanna, based in Pennsylvania, is looking for a Quantitative Researcher who will design and implement statistical and machine learning models. The role involves large-scale data analysis, model evaluations, and collaboration with traders to enhance trading strategies.

Ideal candidates are PhD graduates by Summer 2026 in quantitative fields. Strong programming skills in Python, along with analytical problem-solving abilities, are key qualifications for success in this dynamic environment.

Qualificações

  • PhD graduates or postdocs in mathematics, physics, statistics, etc.
  • Analytical problem-solvers with logical reasoning skills.
  • Effective communicators in collaborative environments.
  • Experience in programming for data processing.
  • Strategic thinkers interested in competitive activities.

Responsabilidades

  • Apply statistical and machine learning techniques for model building.
  • Optimize existing strategies and propose improvements.
  • Backtest ideas using historical market data and research clusters.
  • Participate in a comprehensive education program.

Conhecimentos

Statistical analysis
Machine learning
Python programming
C++ programming
Analytical problem-solving
Clear communication

Formação académica

PhD or postdoc in quantitative fields

Descrição da oferta de emprego

SIG Susquehanna, based in Pennsylvania, is looking for a Quantitative Researcher who will design and implement statistical and machine learning models. The role involves large-scale data analysis, model evaluations, and collaboration with traders to enhance trading strategies.

Ideal candidates are PhD graduates by Summer 2026 in quantitative fields. Strong programming skills in Python, along with analytical problem-solving abilities, are key qualifications for success in this dynamic environment.

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