Data Scientist / Quantitative Researcher – High Frequency Futures

| Chicago

Position Summary

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.

 

Responsibilities

• 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.

 

Requirements

At least 2+ years of experience generating or implementing short-term trading alphas into production trading strategies.

• 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 an in object oriented language is a plus.

 

About Wolverine

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 offices in New York and San Francisco and a proprietary trading affiliate office located in London.

 

Sponsorship is not available for this position.

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Technology we use

  • Engineering
    • .NETLanguages
    • C#Languages
    • C++Languages
    • PythonLanguages
    • RLanguages
    • SqlLanguages

Location

Chicago's Financial District: we are within walking distance to all of the exchanges and conveniently located for commuting from all over Chicago

What are Wolverine Trading Perks + Benefits

Wolverine Trading Benefits Overview

THE BASICS
Highly competitive salary
Medical, Dental, Vision, and Life insurance
Long and short-term disability
Retirement plans: 401k and Roth 401k
Profit sharing plan
Generous vacation days

ABOVE & BEYOND
Casual dress
Free, chef staffed kitchen
Teambuilding activities
Monthly social events
Company subsidized gym in building

Culture
Volunteer in Local Community
Friends Outside of Work
Eat lunch together
Intracompany Committees
Daily Stand Up
Open Door Policy
Team-Owned Deliverables
Team-Based Strategic Planning
Group Brainstorming Sessions
Pair Programming
Open Office Floor Plan
Diversity
Highly Diverse Management Team
Unconscious Bias Training
Health Insurance & Wellness Benefits
Disability Insurance
Dental Benefits
Vision Benefits
Health Insurance Benefits
Life Insurance
Wellness Programs
Onsite Gym
Retirement & Stock Options Benefits
401(K)
Performance Bonus
Child Care & Parental Leave Benefits
Generous Parental Leave
Family Medical Leave
Company Sponsored Family Events
Vacation & Time Off Benefits
Generous PTO
Paid Holidays
Paid Sick Days
Perks & Discounts
Casual Dress
Company Outings
Acme Co. hosts company outings Monthly.
Free Daily Meals
Stocked Kitchen
Happy Hours
Recreational Clubs
Relocation Assistance
Fitness Subsidies
Professional Development Benefits
Lunch and Learns
Cross-Functional Training Encouraged
Promote From Within
Mentorship Program
Time Allotted For Learning
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