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Quantitative Finance Physics Phd Jobs (NOW HIRING)

... • BA/BS/MS/PhD degree in Computer Science, Data Science, Engineering, Math, Economics, Finance, Physics, or related field • Exceptional attention to detail • Excellent quantitative and ...

MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline * 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed ...

MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline * 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed ...

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Quantitative Finance Physics Phd information

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$146K

How much do quantitative finance physics phd jobs pay per year?

As of Aug 9, 2026, the average yearly pay for quantitative finance physics phd in the United States is $90,579.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $119,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a quantitative finance physics PhD?

To thrive as a Quantitative Finance Physics PhD, you need advanced mathematical modeling, statistical analysis, and programming skills, typically supported by a PhD in physics, mathematics, or a related quantitative field. Familiarity with technical tools such as Python, MATLAB, R, and financial systems like Bloomberg Terminal, along with knowledge of financial theories and possibly certifications like CFA, is highly valued. Strong problem-solving abilities, critical thinking, and effective communication set top candidates apart in this competitive field. These competencies are crucial for developing robust financial models, interpreting complex data, and making informed investment decisions in high-stakes environments.

What is a quantitative finance physics PhD?

A Quantitative Finance Physics PhD is a professional who holds a doctoral degree in physics and works in quantitative finance, often as a 'quant.' They use advanced mathematical, statistical, and computational methods—skills developed during their physics training—to analyze financial markets, develop pricing models, and manage risk. Their strong background in problem-solving and data analysis makes them valuable in roles such as quantitative analyst, risk manager, or algorithmic trader within banks, hedge funds, and financial institutions.

How do physics PhDs typically transition their skills into the collaborative environment of a quantitative finance team?

Physics PhDs often bring advanced analytical and problem-solving skills to quantitative finance, but adapting to the collaborative and fast-paced nature of finance teams can be a new challenge. In this role, you'll frequently work alongside software engineers, traders, and other quantitative analysts, combining your mathematical modeling background with financial data analysis. Successful adaptation involves learning industry-specific programming languages (like Python or C++), understanding financial products, and embracing continuous communication to align your models with business objectives. Team members typically value curiosity, the ability to explain complex concepts clearly, and openness to feedback, all of which help foster innovation and drive results.
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What job categories do people searching Quantitative Finance Physics Phd jobs look for? The top searched job categories for Quantitative Finance Physics Phd jobs are:
Infographic showing various Quantitative Finance Physics Phd job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution, with an average salary of $90,579 per year, or $43.5 per hour.

Quantitative Researcher - Internship

WallStreetQuants

New York, NY • On-site

Internship

Posted 25 days ago


Job description

About the Internship

A New York based Hedge Fund is seeking an Undergraduate Quantitative Research Intern to join their quantitative research team. This internship is designed for undergraduate students interested in applying mathematics, statistics, programming, and data analysis to financial markets.

You will work alongside experienced researchers and traders to explore market data, test research ideas, and help evaluate systematic trading strategies. This is a hands-on opportunity to gain exposure to quantitative finance in a collaborative and intellectually challenging environment.

Requirements

Responsibilities
  • Analyze financial and market datasets using statistical methods.
  • Assist with research on systematic trading strategies.
  • Clean, organize, and validate large datasets.
  • Build simple models and backtests under researcher supervision.
  • Write Python code for data analysis, visualization, and research workflows.
  • Summarize findings clearly through charts, reports, or presentations.
  • Collaborate with researchers, traders, and engineers on research projects.
  • Learn how quantitative research ideas are developed, tested, and evaluated.
Qualifications
  • Currently pursuing a bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, or a related quantitative field.
  • Expected graduation date of 2028 or 2029.
  • Strong academic performance in quantitative coursework.
  • Programming experience in Python.
  • Familiarity with probability, statistics, linear algebra, or optimization.
  • Interest in financial markets, trading, investing, or data-driven decision-making.
  • Strong problem-solving skills and attention to detail.
  • Ability to communicate technical ideas clearly.
Preferred Qualifications
  • Experience with pandas, NumPy, matplotlib, scikit-learn, or similar tools.
  • Coursework or projects involving data analysis, machine learning, econometrics, or time series.
  • Familiarity with SQL or databases.
  • Participation in math, programming, trading, data science, or research competitions.
  • Prior internship, academic research, or independent project involving quantitative analysis.

Benefits

What You’ll Gain
  • Exposure to real-world quantitative research and systematic trading.
  • Mentorship from experienced researchers and traders.
  • Practical experience working with financial data.
  • Opportunity to contribute to meaningful research projects.
  • A deeper understanding of careers in quantitative finance.