Data Scientist - US Equity Options Market Making | Growth & Perks

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

Medical, dental, vision benefits

401(k) and Roth 401(k)

Parental leave

On-site gym

Free breakfast & lunch

Team outings

Job summary

Wolverine Trading, LLC in Chicago, IL is hiring a Data Scientist to join our Trading department. You will help disseminate liquidity across US Equity Options markets, build experiments, and analyze order flow dynamics.

You will curate results for traders and engineers, suggest feature enhancements, and work with large-scale datasets to improve strategy performance. This role emphasizes learning and collaboration in a fast-paced environment.

Qualifications

• Background in a quantitative field.
• Understanding of basic statistical concepts such as regression analysis.
• Experience with Python and common data science packages.
• Willingness to learn C#; OO programming is a plus.
• Interest in low-level networking and FPGA concepts.
• Strong technical and non-technical communication skills.

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 enhancements and parameter configurations via post-trade analytics.
• Work with large tick databases to build and maintain core datasets for productivity and strategy enhancements.

Skills

Quantitative background

Statistics basics (regression)

Python & data science packages

Object-oriented programming

C# willingness to learn

Networking/FPGA concepts

Communication skills

Job description

Wolverine Trading, LLC in Chicago, IL is hiring a Data Scientist to join our Trading department. You will help disseminate liquidity across US Equity Options markets, build experiments, and analyze order flow dynamics.

You will curate results for traders and engineers, suggest feature enhancements, and work with large-scale datasets to improve strategy performance. This role emphasizes learning and collaboration in a fast-paced environment.