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Quantitative Risk Intern Jobs in Philadelphia, PA

Quantitative Risk Intern information

What are the key skills and qualifications needed to thrive as a Quantitative Risk Intern, and why are they important?

To thrive as a Quantitative Risk Intern, you need strong analytical skills, a solid understanding of statistics and probability, and progress toward a degree in finance, mathematics, or a related field. Familiarity with programming languages like Python or R, experience using statistical software, and knowledge of risk management frameworks are typically expected. Attention to detail, effective communication, and a proactive approach to problem-solving are valuable soft skills in this role. These competencies are crucial for accurately assessing financial risks and supporting data-driven decision-making in a fast-paced environment.

What types of projects or tasks can a Quantitative Risk Intern expect to work on during their internship?

As a Quantitative Risk Intern, you can expect to contribute to projects involving data analysis, financial modeling, and risk assessment for various portfolios or products. Typical tasks include gathering and cleaning large datasets, running statistical analyses, developing or refining risk models under supervision, and preparing reports to communicate findings to senior team members. Interns often collaborate closely with risk analysts, quantitative researchers, and sometimes IT teams, gaining exposure to both technical and business aspects of risk management. This hands-on experience provides valuable insight into industry-standard tools and methodologies, preparing you for a potential full-time role in quantitative finance.

What are Quantitative Risk Interns?

Quantitative Risk Interns are students or recent graduates who assist risk management teams in financial institutions by applying mathematical, statistical, and programming skills to analyze and manage financial risks. They typically work on projects that involve modeling risk exposures, stress testing portfolios, and supporting the development of risk management tools. This role provides hands-on experience with risk assessment processes, financial data analysis, and exposure to industry-standard software and methodologies. Interns also have the opportunity to learn from experienced risk professionals and gain insight into the decision-making processes that help institutions mitigate financial risks.
What job categories do people searching Quantitative Risk Intern jobs in Philadelphia, PA look for? The top searched job categories for Quantitative Risk Intern jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Quantitative Risk Intern jobs? Cities near Philadelphia, PA with the most Quantitative Risk Intern job openings:
Infographic showing various Quantitative Risk Intern job openings in Philadelphia, PA as of July 2026, with employment types broken down into 14% Internship, 1% As Needed, 47% Full Time, 35% Part Time, 2% Temporary, and 1% Contract. Highlights an 92% Physical, 4% Hybrid, and 4% Remote job distribution.
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Posted 17 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.
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