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Applied Mathematics Phd Jobs in Utah (NOW HIRING)

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Applied Mathematics Phd information

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$20.5K

$53.6K

$86K

How much do applied mathematics phd jobs pay per year?

As of Aug 28, 2026, the average yearly pay for applied mathematics phd in Utah is $53,564.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $63,700.00 per year, depending on experience, location, and employer.

What is an applied mathematics PhD?

Applied Mathematics PhDs are advanced academic degrees focused on the development and application of mathematical methods to solve real-world problems in science, engineering, business, and other fields. Students in these programs engage in research that often bridges theoretical mathematics and practical applications, such as modeling physical phenomena, analyzing data, or optimizing systems. Graduates are equipped to work in academia, industry, government, or research institutions, contributing mathematical expertise to a wide range of disciplines.

What types of projects or research areas do applied mathematics PhDs typically work on within industry settings?

Applied Mathematics PhD holders often work on projects involving data analysis, mathematical modeling, algorithm development, and optimization in industries such as finance, technology, healthcare, and engineering. They may collaborate with interdisciplinary teams to solve complex real-world problems, such as developing predictive models, optimizing processes, or designing simulations. These roles often require strong communication skills to translate mathematical concepts into practical solutions for stakeholders. The work environment is typically collaborative, with opportunities to lead projects or move into specialized or managerial positions over time.

What are the key skills and qualifications needed to thrive as an applied mathematics PhD, and why are they important?

To thrive as an Applied Mathematics PhD, you need advanced mathematical modeling, analytical thinking, and quantitative problem-solving skills, typically supported by a doctoral degree in mathematics or a related field. Familiarity with programming languages (such as Python, MATLAB, or R), statistical software, and experience with computational tools is often required. Strong communication, collaboration abilities, and adaptability are essential soft skills for conveying complex concepts and working in multidisciplinary teams. These skills are crucial for developing innovative solutions to real-world problems and effectively contributing to academic, industrial, or research environments.

What is the difference between Applied Mathematics Phd vs Data Scientist?

AspectApplied Mathematics PhdData Scientist
Required CredentialsPhD in Applied Mathematics or related fieldBachelor's or Master's in Computer Science, Statistics, or related field; some roles prefer PhD
Work EnvironmentResearch labs, academia, industry R&DTech companies, finance, healthcare, consulting
Industry UsageModel development, algorithm design, researchData analysis, predictive modeling, business insights
Common Search/ComparisonApplied Mathematics Phd vs Data Scientist

While both roles involve data analysis and modeling, Applied Mathematics Phds focus more on theoretical research and developing new algorithms, often in research or academic settings. Data Scientists typically apply existing models to solve business problems in industry. The roles overlap in quantitative skills but differ in focus and work environment.

Are applied mathematics PhDs in demand?

Applied mathematics PhDs are in demand across industries such as finance, data science, engineering, and research, where advanced analytical and problem-solving skills are valued. These roles often require strong programming, statistical, and modeling expertise, with employment opportunities available in academia, government, and private sectors.

Is an applied mathematics PhD worth it?

An applied mathematics PhD can lead to careers in research, data analysis, finance, and academia, often requiring strong analytical and programming skills. While it offers advanced expertise, the value depends on career goals and industry demand, which can vary by field and location.

What can I do with a PhD in applied mathematics?

A PhD in applied mathematics prepares individuals for research, data analysis, and modeling roles across industries such as finance, engineering, technology, and academia. Graduates often work as quantitative analysts, data scientists, operations researchers, or in roles requiring advanced problem-solving and programming skills with tools like MATLAB, Python, or R.

What are popular job titles related to Applied Mathematics Phd jobs in Utah?

For Applied Mathematics Phd jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Applied Mathematics Phd jobs in Utah look for?

The top searched job categories for Applied Mathematics Phd jobs in Utah are:

What cities in Utah are hiring for Applied Mathematics Phd jobs?

Cities in Utah with the most Applied Mathematics Phd job openings:

Applied Mathematics Phd jobs near you
Infographic showing various Applied Mathematics Phd job openings in Utah as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $53,564 per year, or $25.8 per hour.

Vice President, Quantitative Engineering

Salt Lake City, UT • On-site

Agupdate
See more jobs at Agupdateexternal

$180 - $260/hr

Other

Posted 7 days ago

Job description

Vice President, Quantitative Engineering w/ Goldman Sachs & Co. LLC in Salt Lake City, Utah. Lead the development, implementation, and documentation of scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Job Code: 10412228

Requires:
  • Master's degree (U.S. or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Computational Finance, Applied Mathematics, or related quantitative field and three (3) years of experience in job offered or a related quantitative engineering role
  • Bachelor's degree (U.S. or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Computational Finance, Applied Mathematics, or related quantitative field and five (5) years of experience in job offered or a related quantitative engineering role
  • PhD degree (U.S. or foreign equivalent) in Mathematics, Computer Science, Financial Engineering, Computational Finance, Applied Mathematics, or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role

Prior experience must include three (3) years of experience (with a Master's degree) OR five (5) years of experience (with a Bachelor's degree) OR one (1) year of experience (with a PhD degree) with 5 of the 8 following skills:

  • C++, Java, or Python
  • performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques
  • performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts
  • object-oriented programming and scripting programming languages such as Python or Java
  • implementing mathematical models or analytics in production-quality software
  • working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets
  • applying algorithms or data structures to write complex programs
  • and developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments

©The Goldman Sachs Group, Inc., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.

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