Quantitative Researcher

Edgehog Trading is a proprietary trading firm specializing in electronic options market making. We take a technology-driven approach, designing and operating automated, scalable systems to provide liquidity across markets.

Our team spans trading, engineering, and business operations, working together to build and support the systems that power the firm. We emphasize data-driven decision making, rigorous problem solving, and continuous improvement to navigate complex and evolving markets.

We operate in a highly collaborative environment where ideas can move quickly from concept to implementation, and where individuals are empowered to take ownership and contribute directly to the firm’s growth.

• →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 closely with traders and engineers to translate research findings into live trading systems
• →Use AI tools actively throughout your research workflow — from exploring datasets and generating hypotheses to accelerating code and stress-testing model assumptions
• →Contribute to research infrastructure: data pipelines, evaluation frameworks, and reproducibility tooling

• BS, MS, or PhD in a quantitative field — Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar
• 1–3 years of research or industry experience in quantitative finance, systematic trading, or applied ML / data science
• Strong programming skills in Python; comfort with numerical libraries (NumPy, pandas, SciPy) and data analysis at scale
• Solid foundation in probability, statistics, and machine learning
• Ability to think rigorously about model assumptions, overfitting risks, and out-of-sample validation
• Comfort with AI-assisted development: you actively use LLMs and other AI tools to move faster, think more clearly, and build better
• Genuine curiosity about markets, trading, and how quantitative systems interact with real-world price dynamics
• Candidates from data science or applied ML backgrounds are welcome — strong modeling instincts and statistical rigor matter more to us than prior finance experience

• Small team advantage: Direct access to founders and senior team members from day one
• Ownership early: Manage real P&L and make meaningful impact within your first year
• Cutting-edge tech: Work with our proprietary models and low-latency trading systems built in-house
• Tight feedback loops: Weekly 1-on-1s with your mentor, quarterly reviews with leadership
• Chicago-based: Affordable cost of living, vibrant trading community