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Phd Statistics Internship Jobs (NOW HIRING)

Stripe

PhD Data Scientist, Intern

San Francisco, CA · On-site

... fellow interns Who you are Minimum requirements We're looking for someone who has: * Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the ...

The Pennsylvania State University

Internship Role: We are seeking a highly motivated PhD intern (part-time research role) to support ... CAMPUS SECURITY CRIME STATISTICS Pursuant to the Jeanne Clery Disclosure of Campus Security Policy ...

SCM

Quantitative Research Analyst Internship

Radnor, PA · On-site

... and PhD levels. Primary Responsibilities * Read and analyze academic research or other source ... Build data sets and conduct statistical analysis on the data. Requirements * Substantial progress ...

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How much do phd statistics internship jobs pay per hour?

As of May 29, 2026, the average hourly pay for 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.

What is a PhD Statistics Internship job?

A PhD Statistics Internship is a temporary, research-focused position designed for doctoral students specializing in statistics or related fields. Interns work on data analysis, machine learning, or statistical modeling projects, often collaborating with researchers and industry professionals. These internships provide hands-on experience applying statistical methods to real-world problems, enhancing both technical and analytical skills. They can be in academia, government, or industry settings, such as technology, healthcare, or finance.

What are the key skills and qualifications needed to thrive in the Phd Statistics Internship position, and why are they important?

To thrive as a PhD Statistics Intern, you need advanced training in statistical theory, data analysis, and research methodology, typically evidenced by ongoing doctoral studies in statistics or a related field. Familiarity with statistical software such as R, Python, SAS, or MATLAB, and experience with data visualization and database management platforms, are important technical assets. Strong analytical thinking, attention to detail, effective communication skills, and the ability to collaborate within multidisciplinary teams are important soft skills. These competencies are essential for effectively analyzing complex data, generating insights, and contributing to impactful research projects in a professional setting.

What types of projects or research topics do PhD Statistics Interns typically work on during their internship?

PhD Statistics Interns are often assigned to projects that involve analyzing large datasets, developing or improving statistical models, and providing insights for data-driven decision-making. These projects can span a range of industries, including healthcare, finance, technology, or public policy, and may address real-world problems such as predictive modeling, experimental design, or survey analysis. Interns typically work closely with senior statisticians and cross-functional teams, allowing for hands-on experience and professional mentoring. The variety of projects helps interns build practical skills and expand their expertise, often contributing to publishable research or product development.
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Phd Statistics Internship jobs near you
Infographic showing various Phd Statistics Internship job openings in the United States as of May 2026, with employment types broken down into 71% Full Time, and 29% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Posted 20 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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