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From Home Quant Intern Jobs (NOW HIRING)

Akuna Capital

Quantitative Research Intern

Chicago, IL · On-site

$130K/yr

Today, Akuna is proud to operate from additional offices in Sydney, Shanghai, London, and Singapore. What you'll do as a Quantitative Research Intern at Akuna: Akuna's Quant team is looking to add ...

Tumo Designs

Marketing Intern

La Verne, CA

$15 - $20/hr

Marketing Intern - College Credits We are seeking a Marketing Intern to join our fast-paced, creative environment This is a work at home position. Coming to our office is not required.

Scotiabank

Associate Director, Credit Quant

Manhattan, NY · On-site

$120 - $150/hr

Associate Director, Credit Quant Location: United States: New York: New York City Duties The Bank ... Telecommuting and/or working from home may be permissible pursuant to company policies. #J-18808 ...

EdTrust

P-12 Research and Data Intern

Washington, DC · On-site

$25 - $30/hr

The ideal candidate has experience working directly with youth, conducting quantitative and ... Through our research and advocacy, EdTrust improves equity in education from preschool through ...

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All JobsQuant Intern JobsFrom Home Quant Intern Jobs

From Home Quant Intern information

What is the difference between From Home Quant Intern vs From Home Data Analyst?

AspectFrom Home Quant InternFrom Home Data Analyst
Required CredentialsTypically pursuing or holding a degree in finance, mathematics, or related fieldsUsually requires a degree in statistics, data science, or related areas
Work EnvironmentRemote internship within financial firms or hedge fundsRemote or office-based roles in various industries like finance, marketing, or tech
Employer & Industry UsagePrimarily in finance and investment firmsAcross multiple sectors including finance, healthcare, and tech
Common Search & ComparisonOften compared for internship opportunities in quantitative financeCompared for entry-level data analysis roles in various industries

In summary, From Home Quant Interns focus on financial modeling and quantitative research within finance firms, requiring strong math and programming skills. From Home Data Analysts have a broader scope, working across industries analyzing data to inform business decisions, often with similar educational backgrounds but different industry applications.

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Infographic showing various From Home Quant Intern job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, and 4% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 9 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)