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Statistical Analysis Intern Jobs (NOW HIRING)

EV Realty

Intern, Data Analytics

San Francisco, CA · On-site +1

Develop Python/SQL scripts for data analysis, automation, and supporting analytical workflows ... Currently pursuing a Bachelor's degree in Data Science, Statistics, Computer Science, GIS, Business ...

EV Realty

Intern, Data Analytics

San Francisco, CA · On-site

Develop Python/SQL scripts for data analysis, automation, and supporting analytical workflows ... Currently pursuing a Bachelor's degree in Data Science, Statistics, Computer Science, GIS, Business ...

NinjaHoldings

Risk & Analytics Intern

Chicago, IL · On-site +1

$20 - $25/hr

Conduct analysis using advanced data analytics to evaluate trends in funnel and loan performance ... Current junior or incoming senior majoring in Mathematics, Statistics, Computer Science ...

New

ZURU

Data Analyst Intern

Los Angeles, CA · On-site

$20 - $25/hr

We're looking for a data analyst intern to join our LA based team! If you're a problem-solving pro ... Familiar with SQL, Data Visualization, Statistical Analysis, Python Programming, ETL practices. * A ...

ZURU

Data Analyst Intern

El Segundo, CA · On-site

$20 - $25/hr

We're looking for a data analyst intern to join our LA based team! If you're a problem-solving pro ... What You'll Bring * * Familiar with SQL, Data Visualization, Statistical Analysis, Python ...

ZURU

Data Analyst Intern

El Segundo, CA · On-site

$20 - $25/hr

We're looking for a data analyst intern to join our LA based team! If you're a problem-solving pro ... What You'll Bring * * Familiar with SQL, Data Visualization, Statistical Analysis, Python ...

IBM

As an intern, you may: * Develop scalable analytical solutions that provide data-driven and ... Experience with statistical analysis such as linear models, multivariate analysis, clustering, time ...

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Statistical Analysis Intern information

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How much do statistical analysis intern jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for statistical analysis intern in the United States is $37.15, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $56.25 per hour, depending on experience, location, and employer.

What does a statistical analysis intern do?

A Statistical Analysis Intern assists with collecting, organizing, and analyzing data to support business or research objectives. They use statistical techniques to identify trends, patterns, and insights within datasets, often using software such as Excel, R, or Python. Interns may also help prepare reports, visualizations, and presentations based on their findings. This role provides practical experience in applying statistical methods and interpreting results under the guidance of experienced analysts or statisticians.

What are the key skills and qualifications needed to thrive as a statistical analysis intern?

To thrive as a Statistical Analysis Intern, you need a solid understanding of statistics, data analysis, and proficiency in mathematics, typically supported by coursework or a degree in a quantitative field. Familiarity with statistical software such as R, Python, or SAS, as well as experience with data visualization tools, is highly valuable. Strong attention to detail, critical thinking, and clear communication help interns interpret data effectively and share insights with teams. These skills and qualities are crucial for providing accurate analyses that drive informed business or research decisions.

What are some common challenges faced by statistical analysis interns during their internship?

Statistical Analysis Interns often encounter challenges such as learning to work with large, complex datasets and adapting to new statistical software or programming languages. They may also need to interpret ambiguous data or results and communicate their findings clearly to non-technical team members. Collaboration with experienced analysts and seeking feedback can help interns overcome these challenges and build practical skills for future roles.

Which internship is best for statistical analysis students?

The best internships for statistical analysis students are those offered by data-driven companies, research institutions, or government agencies that focus on data analysis, modeling, and interpretation. These internships often require proficiency in tools like R, Python, or SAS and may include opportunities to develop skills in data visualization and statistical programming. Selecting internships with structured training and mentorship can enhance practical experience and career prospects.
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Statistical Analysis Intern jobs near you
Infographic showing various Statistical Analysis Intern job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $77,276 per year, or $37.2 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Cambridge, MA • On-site

Risk Analytics Company
See more jobs at Risk Analytics Companyexternal

Full-time

Re-posted 8 days ago

Key responsibilities

  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches

  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk

  • Design and implement analytical tools and pipelines using Python and SQL

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)