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Summer Intern Applied Mathematics Jobs (NOW HIRING)

Caltech

KISS Summer Intern

Pasadena, CA · On-site

$22 - $28/hr

... study programs, symposia, and applied research initiatives that shape the future of space ... Under the direction of the KISS Executive Director, the summer intern will support three areas of ...

Goosehead

Summer Intern - Transformation

Westlake, OH

$14 - $16.75/hr

Support applied AI and automation pilots end to end - preparing and exploring data, testing ... Own a defined project for the summer and present your findings and recommendations to senior ...

Timber Age

2026 TAS Summer Intern

Durango, CO · On-site

$12 - $20/hr

Basic math skills. * Physical dexterity. * Availability for shift work. Benefits Timber Age is committed to providing asafe, challenging andrewarding work environment. A Summer Intern will receive ...

PLASTPRO 2000 INC

Summer Intern

Los Angeles, CA · On-site

$20/hr

SUMMARY The Business Intern will gain hands-on experience across multiple business functions ... applied experience in core business disciplines Strengthen skills in communication, analytics, and ...

JM Eagle

Summer Intern

Los Angeles, CA · On-site

$20/hr

SUMMARY The Business Intern will gain hands-on experience across multiple business functions ... applied experience in core business disciplines Strengthen skills in communication, analytics, and ...

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Summer Intern Applied Mathematics information

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$11

$19

$34

How much do summer intern applied mathematics jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for summer intern applied mathematics in the United States is $19.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $21.63 per hour, depending on experience, location, and employer.

What are the big 4 internships?

The 'Big 4' internships typically refer to summer internship programs offered by the four largest professional services firms: Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY), and KPMG. These internships are highly competitive and focus on areas such as audit, consulting, advisory, and tax, providing valuable experience for students pursuing careers in finance, accounting, and applied mathematics.

What types of projects can a Summer Intern in Applied Mathematics expect to work on, and how are these projects typically structured?

As a Summer Intern in Applied Mathematics, you can expect to engage in projects that involve data analysis, modeling, algorithm development, or optimization tasks relevant to the organization's needs. These projects are often collaborative and may pair you with a mentor or a small team of researchers or engineers. You'll likely participate in regular meetings to discuss progress, troubleshoot challenges, and present your findings. This structure provides a supportive learning environment while giving you the opportunity to apply mathematical theories to real-world problems.

Which internship is best for maths students?

The best internship for maths students depends on their interests and career goals, but roles such as data analysis, quantitative research, or applied mathematics internships are highly relevant. These internships often involve skills in programming, statistical software, and problem-solving, providing practical experience in fields like finance, technology, or research. Selecting an internship that offers mentorship and exposure to real-world applications enhances career development in mathematics-related fields.

What are the key skills and qualifications needed to thrive as a Summer Intern in Applied Mathematics, and why are they important?

To thrive as a Summer Intern in Applied Mathematics, you need a solid understanding of mathematical concepts, problem-solving abilities, and coursework in calculus, linear algebra, or statistics. Familiarity with programming languages such as Python or MATLAB and experience using mathematical modeling or statistical analysis tools are typically required. Strong analytical thinking, effective communication, and eagerness to learn help interns stand out in collaborative and research-driven environments. These skills are essential for tackling real-world quantitative challenges and contributing meaningfully to projects during the internship.

What can I do with my applied mathematics degree?

A Summer Intern in Applied Mathematics can pursue careers in data analysis, quantitative research, finance, engineering, or software development. The degree provides skills in problem-solving, modeling, and programming with tools like MATLAB, Python, or R, which are valuable across many industries. Internships often lead to full-time roles in research, analytics, or technical consulting.

What does a Summer Intern in Applied Mathematics do?

A Summer Intern in Applied Mathematics typically works on mathematical modeling, data analysis, and problem-solving projects under the guidance of senior mathematicians or scientists. Their tasks may include conducting research, analyzing datasets, developing algorithms, and preparing reports or presentations. Interns often collaborate with multidisciplinary teams and gain practical experience applying mathematical concepts to real-world problems in fields such as engineering, finance, or technology.

What is the difference between Summer Intern Applied Mathematics vs Summer Intern Data Science?

AspectSummer Intern Applied MathematicsSummer Intern Data Science
Required CredentialsMathematics coursework, programming skillsStatistics, programming, data analysis
Work EnvironmentResearch labs, finance, tech companiesTech firms, consulting, finance
Employer & Industry UsageAcademic, finance, engineeringTech, finance, healthcare

Summer Intern Applied Mathematics typically focuses on mathematical modeling, algorithms, and problem-solving, often in finance or engineering sectors. In contrast, Summer Intern Data Science emphasizes data analysis, machine learning, and statistical modeling. Both roles require programming skills and are common in tech and finance industries, but they differ in their core focus and application areas.

Is applied maths in demand?

Applied mathematics is in high demand across industries such as finance, data analysis, engineering, and technology, where skills in modeling, statistical analysis, and programming are valued. Interns with knowledge of tools like MATLAB, Python, or R are often sought after, and the field offers strong employment prospects for those with relevant expertise.
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What states have the most Summer Intern Applied Mathematics jobs? States with the most job openings for Summer Intern Applied Mathematics jobs include:
What job categories do people searching Summer Intern Applied Mathematics jobs look for? The top searched job categories for Summer Intern Applied Mathematics jobs are:
Summer Intern Applied Mathematics jobs near you
Infographic showing various Summer Intern Applied Mathematics job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 59% Full Time, 37% Part Time, 1% Temporary, and 1% Nights. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $40,232 per year, or $19.3 per hour.

Ph.D. Graduate Intern Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 7 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 applyespecially 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 Youll 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)