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Quantitative Developer Intern Jobs (NOW HIRING)

Advantest

Application Engineering Intern

Richardson, TX · On-site

$15 - $19.75/hr

... Engineering team. In this role, the intern will have the opportunity to learn and grow their ... quantitative skills while doing test program debugging and development. They will also work on ...

Gemma Power Systems

Civil Field Engineer Intern

Austin, TX · On-site

$17 - $22.25/hr

Civil Field Engineer Intern Location: TX (exact location depends on assigned project) Employment ... Conduct field verification of quantities installed for Quantitative Performance Report (QPR)

Advantest

Application Engineering Intern

Richardson, TX · On-site

$15 - $19.75/hr

... Engineering team. In this role, the intern will have the opportunity to learn and grow their ... quantitative skills while doing test program debugging and development. They will also work on ...

Littelfuse, Inc.

High School Engineering Intern

Champaign, IL · On-site

$16.75 - $21.75/hr

The High School Engineering Intern - will setup, perform, and troubleshoot a variety of engineering ... The Intern will also accurately report both quantitative and qualitative test data to ensure the ...

Littelfuse

High School Engineering Intern

Champaign, IL

$16.75 - $21.75/hr

The High School Engineering Intern - will setup, perform, and troubleshoot a variety of engineering ... The Intern will also accurately report both quantitative and qualitative test data to ensure the ...

BARRDAY CORP

Engineering Intern

Charlotte, NC · On-site

$15 - $17/hr

Position Overview We are seeking a motivated and detail-oriented Industrial Engineer Intern to ... Key Responsibilities · Perform quantitative and qualitative analysis of manufacturing processes to ...

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Quantitative Developer Intern information

What is a Quantitative Developer Intern job?

A Quantitative Developer Intern works at the intersection of finance, mathematics, and software development. They assist in building, optimizing, and maintaining quantitative models and trading systems. Their responsibilities typically include writing efficient code, working with large datasets, and collaborating with quantitative researchers and traders. The role requires strong programming skills (often in Python, C++, or Java) and a solid understanding of algorithms, data structures, and financial concepts. Interns gain hands-on experience in financial technology and quantitative finance, preparing them for full-time quant developer roles.

What are the key skills and qualifications needed to thrive in the Quantitative Developer Intern position, and why are they important?

To thrive as a Quantitative Developer Intern, you need strong programming skills (particularly in Python, C++, or Java), a solid background in mathematics or statistics, and enrollment in or completion of a relevant degree such as computer science, mathematics, or engineering. Familiarity with data analysis libraries (e.g., NumPy, pandas), version control systems (like Git), and basic experience with financial modeling or quantitative tools is highly valued. Excellent problem-solving abilities, attention to detail, and effective communication skills help interns collaborate across teams and convey complex ideas clearly. These competencies enable quick adaptation to the fast-paced environment, accurate implementation of quantitative models, and effective teamwork in supporting financial decision-making.

What types of projects or tasks do Quantitative Developer Interns typically work on during their internship?

Quantitative Developer Interns often work on developing and optimizing algorithms for data analysis, back-testing trading strategies, or building tools for financial model implementation. You may collaborate with quantitative analysts and senior developers to gather requirements, write and debug code, and assist with the integration of new models into production systems. Projects frequently involve handling large datasets, automating data pipelines, and conducting performance testing of code. These experiences allow interns to gain hands-on exposure to real-world financial technology challenges while contributing meaningfully to team goals.
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Quantitative Developer Intern jobs near you
Infographic showing various Quantitative Developer Intern job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, 7% Part Time, and 18% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 24 days ago

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)