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Phd Math Finance Jobs (NOW HIRING)

Susquehanna

You'll apply your technical expertise in machine learning and data science to real-world financial ... Applied Mathematics, or a closely related field * Proven experience applying machine learning ...

Jump Trading

We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific ... global financial markets. Our culture is unique. Constant innovation requires fearlessness ...

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Phd Math Finance information

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$10

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$59

How much do phd math finance jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for phd math finance in the United States is $25.44, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $29.09 per hour, depending on experience, location, and employer.

What is a PhD in math finance?

A PhD in Math Finance is a doctoral degree focused on the application of advanced mathematical methods to solve complex problems in finance. Students in this program study topics such as stochastic calculus, financial modeling, quantitative risk management, and derivative pricing. The degree prepares graduates for research, academic careers, or high-level quantitative roles in the finance industry, such as quantitative analyst or risk manager. It typically involves original research culminating in a dissertation.

What types of projects or research topics do PhD math finance professionals typically work on within the industry?

PhD Math Finance professionals are often involved in developing quantitative models for pricing complex financial instruments, managing risk, and optimizing investment strategies. Their work may include statistical analysis of market data, stochastic modeling, and algorithmic trading system development. Collaboration with traders, risk managers, and software engineers is common to ensure models are both theoretically sound and practically implementable. These roles offer opportunities to contribute to cutting-edge research while solving real-world financial challenges, and can provide a pathway to leadership positions in quantitative research or risk management.

What are the key skills and qualifications needed to thrive as a PhD in mathematical finance, and why are they important?

To thrive as a PhD in Mathematical Finance, you need advanced quantitative skills, expertise in stochastic calculus and financial modeling, and a doctoral degree in a related field. Proficiency with programming languages like Python, R, or MATLAB, and familiarity with financial databases and risk management systems, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set top candidates apart. These skills enable professionals to develop complex models, interpret financial data, and communicate insights to drive decision-making in finance.

What is the difference between Phd Math Finance vs Quantitative Analyst?

AspectPhd Math FinanceQuantitative Analyst
Required CredentialsPhD in Mathematics, Finance, or related fieldBachelor's or Master's in Math, Finance, or related field; sometimes PhD
Work EnvironmentResearch-focused, academic or industry R&DFinancial firms, trading desks, hedge funds
Employer & Industry UsageUniversities, financial institutions, hedge fundsInvestment banks, hedge funds, asset management firms
Common Search & Comparison IntentUnderstanding advanced roles in finance researchPractical financial modeling and trading strategies

While both roles require strong quantitative skills, a Phd Math Finance typically involves research, developing new models, and academic work, whereas a Quantitative Analyst focuses on applying models to trading, risk management, and investment decisions in financial firms.

What are popular job titles related to Phd Math Finance jobs?

For Phd Math Finance jobs, the most frequently searched job titles are:

Infographic showing various Phd Math Finance job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 93% Full Time, 4% Part Time, and 2% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $52,911 per year, or $25.4 per hour.

Machine Learning Internship - PhD: 2027

Susquehanna
See more jobs at Susquehannaexternal

Full-time, Internship

Posted 11 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.

If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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