Quantitative Finance Research Assistant information
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$10.58 - $13.26
1% of jobs
$13.26 - $15.95
8% of jobs
$18 is the 25th percentile. Wages below this are outliers.
$15.95 - $18.64
22% of jobs
The median wage is $20.90 / hr.
$18.64 - $21.33
24% of jobs
$21.33 - $24.02
16% of jobs
$25.08 is the 75th percentile. Wages above this are outliers.
$24.02 - $26.70
13% of jobs
$26.70 - $29.39
10% of jobs
$29.39 - $32.08
5% of jobs
$32.08 - $34.77
2% of jobs
$34.77 - $37.46
0% of jobs
$37.46 - $40.14
0% of jobs
How much do quantitative finance research assistant jobs pay per hour?
As of Sep 10, 2026, the average hourly pay for quantitative finance research assistant in the United States is $23.35, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $26.20 per hour, depending on experience, location, and employer.
Quantitative Finance Research Assistants are professionals who support research teams by analyzing financial data using mathematical models and statistical techniques. They assist in developing and testing algorithms for trading, risk management, or asset valuation. Their work often involves programming, data analysis, and literature review to inform investment strategies or academic research. This role is common in investment banks, hedge funds, and academic institutions.
Quantitative Finance Research Assistants often encounter challenges such as managing large and complex datasets, ensuring data accuracy, and keeping up with rapidly evolving financial models and technologies. Balancing multiple projects with tight deadlines requires strong organizational skills and attention to detail. Collaborating effectively with both researchers and portfolio managers is crucial, as clear communication helps translate technical findings into actionable insights for the team.
To thrive as a Quantitative Finance Research Assistant, you need strong quantitative and analytical skills, a solid foundation in mathematics or statistics, and usually a relevant degree such as in finance, economics, mathematics, or computer science. Familiarity with programming languages like Python, R, or MATLAB, as well as experience with data analysis tools and financial modeling software, is typically required. Attention to detail, problem-solving ability, and effective communication are standout soft skills for this role. These skills and qualities are crucial for producing accurate research, supporting data-driven decision-making, and effectively collaborating on complex financial projects.
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