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Wolverine Trading, LLC

Quantitative Developer - Options Market Making

chicago, IL

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About this opportunity

Wolverine Trading, LLC lists this Quantitative Developer - Options Market Making opportunity in chicago, Illinois. Review the employer’s description below for duties, qualifications and application requirements.

Job description

Quantitative Developer - Options Market Making

Department: Trading

Employment Type: Full Time

Location: Chicago, IL

Description

We are looking for a Quantitative Developer to join an experienced team responsible for disseminating liquidity for over four thousand underlying products across nearly two dozen exchanges in the US Equity Options Market. Successful candidates will have the opportunity to build and grow around a research and experimentation culture, helping to shape the future direction of our analytics suite.

You will learn the intricacies of the US Equity Options Market in areas ranging from order flow dynamics to exchange rules and matching engine mechanics. The successful candidate will have an organized analytical approach to problem solving and a relentless drive for learning through experimentation.

Market makers enhance the stability of our financial system by providing crucial liquidity to the marketplace, and in doing so operate in a highly competitive landscape. We succeed by the quality of our ideas and the rate of our innovation, and you will have the opportunity to make tangible contributions towards this pursuit.

What You'll Do

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 designed to increase team productivity and facilitate strategy enhancements.

What We're Looking For

Background in a quantitative field

Knowledge of basic statistical concepts such as regression analysis

Experience with Python and common data science packages

Experience with object-oriented programming is a plus but not a requirement. A willingness to learn C# is required.

An understanding of or willingness to learn about low-level details relating to networking and FGPAs.

Strong technical and non-technical communication skills

Why Join Us

Our flat organizational structure promotes teamwork across the Firm and offers easy access to senior staff. While we work exceptionally well as a team in the office, our bonds are further strengthened through company events, activities and giving back. Volleyball, soccer, hockey, 5K runs, picnic, parties, and trivia nights provide friendly competition and build better relationships. By getting out of our usual environment and doing out-of-the-ordinary things together, we foster creativity and broaden our imaginations to accomplish new challenges.

Benefits:

Highly competitive salary & bonus opportunity

Generous paid time off and flexible scheduling

100% coverage of medical, dental, vision, life, and disability benefits for single coverage

Generous Paid Parental Leave

Retirement Plans: 401K and Roth 401K

Profit sharing plan

Long- and short-term disability

Additional Perks:

Free breakfast and lunch from our in-house kitchen with rotating menus (including snacks!)

On-site gym with a subsidized membership

Frequent company outings

Opportunity to give back to organizations that help individuals in need in the Chicagoland area

Professional Development:

In-house education team - classes and resources are offered for continuous learning opportunities

Mentorship Program through your first six months of employment

The base compensation range for this role is approximately $100,000-$150,000 contingent on experience. Wolverine Trading's total compensation model includes base salary and an annual discretionary bonus.

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Worksite address

chicago, IL, 60290, US

Who can apply

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