Conduct research to develop signals, alpha, and features for options market-making; design, backtest, and deploy quantitative trading models; analyze market microstructure and execution; collaborate with traders and engineers; use AI/LLMs in research; contribute to research infrastructure and data pipelines.
About us
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.
What you'll do:
- 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
Qualifications and skills:
- 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
Why Edgehog:
- 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
Benefits:
- Comprehensive health, dental, and vision insurance with premiums 100% covered by the firm
- 401(k) with a 4% company match
- Unlimited paid time off and sick leave
- Free lunch, coffee, drinks, and snacks
- Commuter benefits
- Monthly happy hours and annual team events
The base salary range for this position is listed below. Base salary represents just one part of overall compensation; all full-time, permanent roles are eligible for a discretionary bonus and benefits, including items in the above list.
The base salary for this role is 120,000 - 175,000 USD per year
Edgehog Trading Chicago, Illinois, USA Office
363 W Erie St, Chicago, Illinois, United States, 60654
Similar Jobs
Fintech • Payments • Financial Services
Join the options trading quant team to design, implement, and improve derivative pricing models (variance swaps, VIX, volatility swaps). Evaluate and stabilize calibrations and Greeks, develop Python research libraries and market-data filters, analyze microstructure for trading ideas, and collaborate with traders to build tools and generate options research.
Top Skills:
C++Python
.png){kind=avatar}
Fintech • Machine Learning • Software • Financial Services
Conduct quantitative research to design, implement, and deploy mathematical trading models. Build custom tools for exploratory analysis, apply rigorous quantitative techniques to solve complex problems, and collaborate with traders and developers to productionize models while maintaining best practices.
Top Skills:
CC++Python
Fintech • Machine Learning • Software • Financial Services
Conduct quantitative research to improve and design trading models, build tooling, implement and deploy models to production, and collaborate with traders and developers to solve complex problems.
Top Skills:
CC++Python
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
