Job summary
Job post source
This job is directly from Tower Research Capital
Job overview
The Quantitative Trader / Researcher role at Tower Research Capital involves developing and deploying algorithmic trading strategies using advanced trading systems to analyze market behavior.
Responsibilities and impact
Daily responsibilities include designing and implementing trading algorithms, researching trading alphas, analyzing market data for patterns, creating analytical tools, and developing exchange simulators.
Compensation and benefits
The anticipated annual base salary range is $120,000-200,000, plus eligibility for a discretionary bonus, with benefits including 5 weeks of paid vacation, free meals, wellness reimbursements, and donation matching.
Experience and skills
Candidates should have a degree in Mathematics, Statistics, or Computer Science, with preferred experience in quantitative trading, strong mathematical and statistical skills, proficiency in back-testing, and strong programming skills in Python or C++.
Career development
There are opportunities for professional growth through innovative trading strategies and exposure to advanced trading technologies.
Work environment and culture
Tower Research Capital promotes a cubicle-free workplace with a casual dress code, emphasizing quality of life and a collaborative environment.
Company information
Founded in 1998, Tower Research Capital is a high-frequency proprietary trading firm known for its advanced trading systems and global presence.
Team overview
The specific team dynamics and size are not detailed, but candidates will join a collaborative trading team focused on algorithmic strategies.
Job location and travel
The position is based in New York City, with a global office presence.
Unique job features
This role offers unique opportunities to develop cutting-edge trading algorithms and work with one of the fastest trading systems in the world.
Company overview
Tower Research Capital is a leading quantitative trading firm that specializes in developing proprietary trading algorithms and strategies to capitalize on market inefficiencies. Founded in 1998 by Mark Gorton, the company leverages cutting-edge technology and data analysis to execute trades across various asset classes, including equities, futures, options, and cryptocurrencies. Tower Research Capital generates revenue through high-frequency trading, market making, and providing liquidity to financial markets. Known for its innovative approach and robust infrastructure, the firm has a significant presence in global financial markets and offers a dynamic environment for professionals in finance, technology, and quantitative research.
How to land this job
Position your resume to showcase your strong mathematical and statistical background, emphasizing any experience with trading algorithms and data analysis, as these are crucial for the Quantitative Trader / Researcher role at Tower Research Capital.
Highlight your proficiency in programming languages like Python or C++, and detail any experience with back-testing, simulation, and statistical techniques mentioned in the job description.
Apply through multiple platforms, including Tower Research Capital's corporate site and LinkedIn, to enhance your chances of being noticed for this competitive position.
Connect with professionals in the trading division at Tower Research Capital on LinkedIn to express your interest in the role and ask insightful questions about their trading strategies or the technologies they use.
Potential ice breakers could include discussing a recent market trend you find interesting or asking for their thoughts on a specific trading algorithm.
Optimize your resume for ATS systems by integrating keywords from the job description such as 'algorithmic trading', 'data analysis', and 'statistical models' to improve your chances of passing initial screenings.
Consider utilizing Jennie Johnson's Power Apply feature, which can streamline your application process by tailoring your resume, identifying optimal application channels, and connecting you with relevant professionals, allowing you to focus on strategic networking.
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