Intraday Systematic Equities Research Scientist

Selby Jennings

New York (NY)

On-site

USD 400,000 - 600,000

Full time

4 days ago
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Job summary

Selby Jennings seeks a highly capable Research Scientist to join an intraday systematic equities team. The role centers on developing predictive models and extracting insights from large, complex data sources, merging machine learning, statistics, and quantitative research to identify alpha opportunities.

Ideal candidates have top-tier academic credentials and experience in rigorous research environments, with strong Python programming and a deep commitment to data quality and reproducible

Qualifications

  • 2-4 years of experience in quantitative research, machine learning research, or closely related field.
  • Strong programming skills in Python and data-intensive research workflows.
  • Outstanding analytical, mathematical, and problem-solving abilities.
  • Experience at leading quantitative hedge funds, proprietary trading firms, top tech companies, or elite research org.

Responsibilities

  • Conduct original alpha research using machine learning, statistical modeling, and data science techniques.
  • Develop predictive models and novel alpha signals from structured and unstructured datasets.
  • Design robust research frameworks and experimental methodologies.
  • Partner with portfolio management to identify and validate investment opportunities.

Skills

Quantitative research
Python
Data analysis
Experiment design

Education

Bachelor's/Master's in CS/Math/Stats/Physics/Engineering

Job description

Selby Jennings seeks a highly capable Research Scientist to join an intraday systematic equities team. The role centers on developing predictive models and extracting insights from large, complex data sources, merging machine learning, statistics, and quantitative research to identify alpha opportunities.

Ideal candidates have top-tier academic credentials and experience in rigorous research environments, with strong Python programming and a deep commitment to data quality and reproducible

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