Quantitative Research Intern information
See Washington salary details
$5K is the 25th percentile. Wages below this are outliers.
$4.7K - $5.3K
3% of jobs
The median wage is $8.4K / yr.
$8.2K - $8.8K
72% of jobs
How much do quantitative research intern jobs pay per month?
As of Aug 20, 2026, the average monthly pay for quantitative research intern in Washington is $7,293.33, according to ZipRecruiter salary data. Most workers in this role earn between $5,000.00 and $8,683.33 per month, depending on experience, location, and employer.
A Quantitative Research Intern typically assists in analyzing large datasets, developing mathematical models, and conducting statistical analysis to support decision-making in fields like finance, technology, or academia. Their responsibilities may include data cleaning, programming, running simulations, and generating reports on findings. Interns work closely with experienced quantitative researchers and may contribute to ongoing research projects or help develop new methodologies. This role is ideal for students or recent graduates with strong analytical skills and an interest in applying mathematics and statistics to solve real-world problems.
As a Quantitative Research Intern, you can expect to work on projects such as developing and backtesting trading algorithms, analyzing large datasets to identify market patterns, or implementing statistical models to forecast financial trends. Interns often collaborate closely with experienced researchers and traders, contributing to both ongoing research initiatives and exploratory projects. These experiences not only enhance technical and analytical skills but also provide exposure to real-world financial problem-solving in a dynamic team environment.
To thrive as a Quantitative Research Intern, you need strong analytical abilities, a solid foundation in statistics and mathematics, and progress toward a degree in a quantitative field such as mathematics, statistics, finance, or computer science. Familiarity with programming languages like Python, R, or MATLAB, and experience using statistical analysis tools or platforms, are typically required. Attention to detail, problem-solving skills, and effective communication set candidates apart in this role. These skills enable you to analyze complex data, generate actionable insights, and clearly present findings to support data-driven decision-making.
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