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Internship Graduate Python Developer Jobs in Boston, MA

Software & Tools -- Build software, automation and engineering tools using C/C++, Python, Linux ... Relevant experience can come from coursework, research, internships, placements, personal projects ...

Graduate Civil Engineer

Burlington, MA ยท Hybrid

$80K - $82K/yr

As a graduate Civil Engineer, you will work alongside our Senior Engineers on projects in the ... Civil Engineering experience; internship experience preferred * Working knowledge of AutoCAD

Graduate Civil Engineer

Burlington, MA ยท On-site

$80K - $82K/yr

As a graduate Civil Engineer, you will work alongside our Senior Engineers on projects in the ... Civil Engineering experience; internship experience preferred * Working knowledge of AutoCAD

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Internship Graduate Python Developer information

See Boston, MA salary details

$14

$63

$93

How much do internship graduate python developer jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for internship graduate python developer in Boston, MA is $63.69, according to ZipRecruiter salary data. Most workers in this role earn between $52.50 and $72.36 per hour, depending on experience, location, and employer.

PhD Graduate Intern Quantitative Portfolio Risk Analytics

Cambridge, MA โ€ข On-site

Other

Re-posted 11 days ago


Job description

Ph.D. Graduate Intern โ€“ 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 applyโ€”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 Youโ€™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)