Quant Researcher — US Equity Options

Wolverine Trading, LLC; Chicago (IL); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Annual discretionary bonus

Generous paid time off

Comprehensive health/dental/vision/ltd

Retirement plans: 401K and Roth 401K

Profit sharing

Long- and short-term disability

Free breakfast and lunch

On-site gym

Frequent company outings

Community outreach opportunities

Job summary

Wolverine Trading, LLC invites a Quantitative Researcher to join its Trading team in Chicago, IL. You will explore US Equity Options market micro-structure, build experimental pipelines, and present findings to traders and engineers.

The role emphasizes learning through experimentation, with opportunities to impact analytics and trading features across a broad dataset and real-time environments.

Qualifications

• Quantitative field background required.
• Experience with Python and data science libraries required.
• Willingness to learn C# and low-level networking/FPGA concepts.

Responsibilities

• Gain domain expertise on US Equity Option exchange micro-structure.
• Propose, run, and maintain production testing pipelines within an experimental framework.
• Curate, document, and present experimentation results to trading and engineering staff.
• Generate ideas for trading feature enhancement and parameter configurations through post-trade analytics.
• Work with large tick databases to build and maintain core datasets to boost team productivity.

Skills

Quantitative background

Statistics basics

Python

Data science

Regression analysis

C# learning

Networking basics

FPGA basics

Tools

Python

C#

Job description

Wolverine Trading, LLC invites a Quantitative Researcher to join its Trading team in Chicago, IL. You will explore US Equity Options market micro-structure, build experimental pipelines, and present findings to traders and engineers.

The role emphasizes learning through experimentation, with opportunities to impact analytics and trading features across a broad dataset and real-time environments.