Stat-Arb Quantitative Researcher

Alexander Chapman

New York (NY)

On-site

USD 150,000 - 230,000

Full time

14 days+
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Job summary

Alexander Chapman is seeking a Quantitative Researcher to develop and enhance Statistical Arbitrage strategies across global markets. You will conduct alpha research, generate predictive signals, and analyze large-scale datasets, collaborating with traders and engineers to deploy production-ready strategies. Strong programming skills in Python required; knowledge of C++ is a plus. An advanced quantitative degree is preferred.

Qualifications

  • Background in statistical arbitrage or systematic equity research.
  • Experience researching alpha signals, portfolio construction, or execution models.
  • Proficient in Python; knowledge of C++ is a plus.

Responsibilities

  • Conduct alpha research and generate predictive signals.
  • Analyze large-scale market and alternative datasets.
  • Collaborate with traders and engineers to deploy production-ready strategies.

Skills

Stat Arb / systematic equity research
Alpha signal research
Python programming
C++ (plus)

Education

Advanced degree in Mathematics/Statistics/CS/Physics/Engineering

Job description

I'm partnering with a leading systematic trading firm looking to hire a Quantitative Researcher to develop and enhance Statistical Arbitrage strategies across global markets.

You'll conduct alpha research, generate predictive signals, analyze large-scale market and alternative datasets, and work closely with traders and engineers to deploy production-ready strategies.

Requirements:
  • Strong background in Statistical Arbitrage or systematic equity research.
  • Experience researching alpha signals, portfolio construction, or execution models.
  • Excellent programming skills in Python (C++ is a plus).
  • Advanced degree in Mathematics, Statistics, Computer Science, Physics, Engineering, or a related quantitative discipline.
  • Proven ability to conduct rigorous research using large datasets.

This is an opportunity to join a highly collaborative, research-driven environment with world-class infrastructure and significant resources dedicated to systematic investing.

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