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Edgehog Trading

Proprietary trading firm for electronic options

Quantitative Researcher

Quantitative ResearchConfirmed live in the last 24 hours
Full-timeChicago, IL, USAIn-person

About the Job

Requirements

  • A BS, MS, or PhD in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Financial Engineering.
  • 1–3 years of research or industry experience in quantitative finance, systematic trading, or applied machine learning/data science.
  • Strong programming skills in Python and comfort with NumPy, pandas, SciPy, and large-scale data analysis.
  • A solid foundation in probability, statistics, and machine learning.
  • Ability to rigorously assess model assumptions, overfitting risks, and out-of-sample validation.
  • Comfort with AI-assisted development, including active use of large language models and other AI tools.
  • Curiosity about markets, trading, and how quantitative systems interact with real-world price dynamics.

Responsibilities

  • Conduct signal, alpha, and feature research to develop models that improve trading strategy performance.
  • Design, backtest, and iterate on quantitative trading models from ideation through production deployment.
  • Analyze market microstructure, execution quality, and options pricing dynamics to identify new research directions.
  • Collaborate with traders and engineers to translate research findings into live trading systems.
  • Use AI tools throughout the research workflow, including exploring datasets, generating hypotheses, accelerating code, and stress-testing model assumptions.
  • Contribute to research infrastructure, including data pipelines, evaluation frameworks, and reproducibility tooling.

Desired Qualifications

  • Candidates from data science or applied machine learning backgrounds are welcome; strong modeling instincts and statistical rigor matter more than prior finance experience.

About the Company

Edgehog Trading

Proprietary trading firm for electronic options

Edgehog Trading is a proprietary trading firm that focuses on electronic option market making strategies. It runs algorithmic trading to post bids and offers in options markets, aiming to profit from small price differences while managing risk through automation and data-driven decisions. The company achieves this with a team that combines traders, developers, and data scientists, all working to scale and automate profitable strategies across markets. The main differentiators are its in-house, data-centered approach and a problem-solving framework that helps it address complex challenges in efficient markets. The goal is to grow and fully automate its profitable strategies to a high level of precision and scale.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Chicago, IL
Founded
2018

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