Quantitative Trader @ Wolverine Trading

Quantitative Finance (1)

We are looking for highly skilled and experienced individuals to join a research effort focused on generating high frequency trading alphas in the futures markets. The ideal candidate has direct experience in the alpha research process and understands the workflow from idea generation to production implementation. This opportunity will provide the right candidate the chance to have a large impact on the direction and productivity of a newly formed effort within a successful proprietary trading firm.

What You'll Do:

Conduct financial data analysis on large datasets to generate profitable trading alphas.
Define key metrics for model validation
Back-testing and production performance monitoring
Contribute to in-house data analysis packages and research framework development
Acquisition of new data sets and cleaning/maintenance of new and existing data sets.
Contribute to futures trading technology stack architecture

What We're Looking For:

At least 2+ years of experience generating or implementing short term trading alphas into production trading strategies
Knowledge of CME and related market microstructure required.
Advanced knowledge of modern statistical and machine learning techniques
Proficiency in a scripting language such as Python, R, or MATLAB.
Proficiency in at least one statistical package and one machine learning package in one of the above languages.
Demonstrated experience working with tick data.
Degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, Engineering, etc.
Experience developing software systems in an object-oriented language is a plus.

All candidates must be eligible to work in the U.S. without sponsorship.

Base salary is $150,000 - $200,000. Base salary is only one part of Wolverine Trading total compensation, which includes an annual discretionary bonus.

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Why Wolverine?

Wolverine Culture:

Our flat organizational structure promotes teamwork across the Firm and offers easy access to senior staff (don't worry, they won't be wearing a suit either). 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.

Wolverine 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

Perks of being at Wolverine:

· 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

About Us:

Founded in 1994, the Wolverine companies comprise a number of diversified financial institutions specializing in proprietary trading, asset management, order execution services, and technology solutions. We are recognized as a market leader in derivatives valuation, trading, and value-added order execution across global equity, options, and futures markets. With a focus on innovation, achievement, and integrity, we take pride in serving the interests of both our clients and colleagues. The Wolverine companies are headquartered in Chicago with an office in New York and a proprietary trading affiliate office located in London.

Quantitative Trader

High Frequency Futures

Wolverine Trading

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