Summer Phd Statistics Internship information
See salary details
$10.47 - $11.80
2% of jobs
$11.80 - $13.13
3% of jobs
$13.13 - $14.47
17% of jobs
$14.55 is the 25th percentile. Wages below this are outliers.
$14.47 - $15.80
18% of jobs
The median wage is $16.51 / hr.
$15.80 - $17.13
16% of jobs
$17.13 - $18.47
11% of jobs
$18.89 is the 75th percentile. Wages above this are outliers.
$18.47 - $19.80
20% of jobs
$19.80 - $21.13
6% of jobs
$21.13 - $22.47
3% of jobs
$22.47 - $23.80
2% of jobs
How much do summer phd statistics internship jobs pay per hour?
As of Aug 26, 2026, the average hourly pay for summer phd statistics internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.
A Summer PhD Statistics Internship is a temporary, typically paid position offered during the summer months to doctoral students specializing in statistics or related fields. Interns work on real-world projects, applying their statistical knowledge to solve business, research, or industry problems. These internships provide hands-on experience, exposure to different statistical methods and software, and valuable networking opportunities. They often serve as a pathway to full-time roles in academia, industry, or research organizations.
Summer PhD Statistics Interns often work on real-world data analysis, model development, or statistical research projects that directly support the company's objectives. These projects may involve collaborating with cross-functional teams, such as data scientists, engineers, or subject matter experts, to solve complex business problems. By engaging in these initiatives, interns gain hands-on experience with industry-standard tools and methodologies, enhance their communication skills, and build a portfolio of impactful work that can benefit their future academic or industry careers.
To thrive as a Summer PhD Statistics Intern, you typically need advanced knowledge of statistical theory, data analysis, and programming, usually as part of a current PhD program in statistics or a related field. Familiarity with statistical software such as R, Python, SAS, or MATLAB, and experience with data visualization tools, is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and present findings clearly. These skills and qualities are essential for delivering high-quality research support, contributing to team projects, and making meaningful insights from data.
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