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Quantitative Finance Physics Phd Jobs (NOW HIRING)

Point72

Macro Quantitative Researcher

New York, NY · On-site

MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics * 4+ years of signal research or portfolio ...

Point72

Cubist Quantitative Researcher

New York, NY · On-site

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 ...

Point72

Cubist Quantitative Researcher

New York, NY · On-site

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

As of Sep 2, 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 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.

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.
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Quantitative Finance Physics Phd jobs near you
Infographic showing various Quantitative Finance Physics Phd job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 4% Part Time, and 2% 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.

Macro Quantitative Researcher

Point72

New York, NY • On-site

Full-time

Re-posted 27 days ago

Job description

About the Team:

A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.

Role:

  • Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets
  • Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space
  • Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
  • Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets

Responsibilities:

  • Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets
  • Alpha idea generation, backtesting, and implementation
  • Evaluate new datasets for alpha potential
  • Contribute to and enhance portfolio optimization, allocation and risk management processes
  • Help drive the growth of the investment process and research capabilities of the team
  • Assist in building, maintenance, and continual improvement of production and trading environments

Requirements:

  • MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
  • 4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record
  • Prior professional experience with signal combination, portfolio optimization and risk management
  • Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
  • Collaborative mindset with strong independent research abilities
  • Commitment to the highest ethical standards

Apply