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$15

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How much do phd probability theory jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for phd probability theory in the United States is $29.44, according to ZipRecruiter salary data. Most workers in this role earn between $25.48 and $32.93 per hour, depending on experience, location, and employer.

What is the difference between Phd Probability Theory vs Data Scientist?

AspectPhd Probability TheoryData Scientist
Required CredentialsPhD in Mathematics, Statistics, or related fieldBachelor's or Master's in Computer Science, Statistics, or related field; some roles prefer PhD
Work EnvironmentAcademic, research institutions, or specialized industry R&DCorporate, tech companies, consulting firms, with focus on data analysis
Industry UsageResearch, academia, quantitative finance, specialized analyticsBusiness, marketing, product development, machine learning applications

While both roles involve advanced analytical skills, a Phd Probability Theory focuses on theoretical research and mathematical modeling, often in academia or specialized industries. Data Scientists apply statistical and machine learning techniques to solve practical business problems, often requiring a broader skill set including programming and data management.

Infographic showing various Phd Probability Theory job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 10% Part Time, and 1% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $61,245 per year, or $29.4 per hour.
Lead Quantitative Developer/Research Engineer

Lead Quantitative Developer/Research Engineer

Intercontinental Exchange Holdings, Inc.

Atlanta, GA • On-site

Full-time

Posted 7 days ago

Job description

Overview
Job Purpose
Research Engineers at ICE are responsible for designing, building, and optimizing quantitative libraries and research platforms that support various business units, including Clearing, Exchange, and Valuation Services. We require strong knowledge of low-level optimization, algorithms, risk management, and application development. Research Engineers will gain exposure to quantitative modeling, pricing, and risk management. They will work on projects from inception through deployment, taking full ownership of what they build.
Responsibilities
  • Design, develop, test, and deploy sophisticated quantitative models for the Exchange and Clearing house across various asset classes.
  • Develop and implement pricing and calibration tools for commodities, interest rates, and other financial derivatives.
  • Design and develop high-performance C++ components used by Clearing, Exchange, and Valuation Services.
  • Partner with the Quantitative Research team to define priorities and deliver custom solutions.
  • Analyze large data sets, including model prices and market data prices.
  • Explain model behavior, provide remediation and analytics.
  • Document methods, techniques, results, and analysis.

Knowledge and Experience
  • A deep passion for mathematics, technology, and software development.
  • Extensive experience in C++.
  • Proficiency in Python.
  • Advanced knowledge of mathematics, including stochastic processes, probability theory, and numerical methods.
  • Exceptional quantitative and analytical skills.
  • Master's or PhD degree in Computer Science, Mathematics, Statistics, or a related field.
  • Strong verbal and written communication skills in English.

Preferred Knowledge and Experience
  • Work experience in options pricing theory
  • Work experience in Data Analytics and Machine Learning
  • 3 Years of experience in a related field.

Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.
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Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.

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