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Phd Math information

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$8

$27

$38

How much do phd math jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for phd math in California is $27.42, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $28.94 per hour, depending on experience, location, and employer.

What are PhD Math graduates qualified to do after earning their degree?

PhD Math graduates are equipped for a range of careers that require advanced mathematical knowledge and research skills. Many pursue academic positions as professors or researchers at universities, while others work in industry roles such as data scientists, quantitative analysts, or mathematicians in government and private sectors. Their expertise is valuable in finance, technology, engineering, and consulting, where complex problem-solving and analytical abilities are essential. Additionally, some contribute to interdisciplinary research, policy analysis, or science communication.

What jobs can a math PhD get?

A math PhD can pursue roles such as data scientist, quantitative analyst, research scientist, operations researcher, or university professor. These positions often require strong analytical, programming, and research skills, and may involve working in finance, technology, academia, or government agencies.

What are the key skills and qualifications needed to thrive as a PhD-level Mathematician, and why are they important?

To thrive as a PhD-level Mathematician, you need advanced expertise in mathematical theory, analytical reasoning, and problem-solving, typically supported by a doctoral degree in mathematics or a related field. Familiarity with programming languages (such as Python or MATLAB), mathematical modeling software, and experience with academic research tools are commonly required. Strong communication, perseverance, and collaboration skills help stand out when presenting findings and working in interdisciplinary teams. These competencies are crucial for contributing original research, solving complex problems, and advancing mathematical knowledge in academic or industry settings.

What is the difference between Phd Math vs Data Scientist?

AspectPhd MathData Scientist
Required CredentialsPhD in Mathematics or related fieldBachelor's or Master's in CS, Stats, or Math; often prefers PhD
Work EnvironmentAcademic, research institutions, or R&D departmentsCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, governmentBusiness analytics, machine learning, data analysis
Common Search/ComparisonYesYes

While both roles require strong analytical skills, a Phd Math typically focuses on theoretical research and academic or research institution work. In contrast, a Data Scientist applies statistical and mathematical techniques to solve practical business problems in industry settings. The credentials overlap, but the work environment and application focus differ significantly.

Is a PhD in math useful?

A PhD in math is highly valuable for careers in academia, research, data science, and quantitative analysis. It demonstrates advanced problem-solving, analytical skills, and expertise in mathematical modeling, which are sought after in various industries. However, its usefulness depends on career goals and the ability to apply mathematical knowledge practically.

What does a PhD in Mathematics get you?

A PhD in Mathematics qualifies individuals for advanced research, teaching at the university level, and roles in data analysis, quantitative finance, or scientific computing. It demonstrates expertise in complex problem-solving, analytical skills, and often requires proficiency with mathematical software and programming languages.

Do math PhDs make good money?

Math PhDs often pursue careers in academia, research, data science, or finance, where salaries can vary widely. In industry roles such as quantitative analysis or data science, they can earn competitive salaries, often higher than those with only a master's degree, especially with experience and specialized skills. However, academic positions may offer lower pay compared to industry roles.

What are the typical collaborative opportunities for someone in a PhD-level mathematics role?

PhD-level mathematicians often work within interdisciplinary teams, collaborating with professionals in fields like computer science, engineering, economics, and data science. These collaborations usually involve joint research projects, problem-solving sessions, or co-authoring academic papers. Mathematicians may also work closely with industry partners to apply theoretical models to real-world challenges, such as optimizing algorithms or analyzing large data sets. This teamwork fosters both professional growth and the opportunity to see the practical impact of mathematical research.
What are popular job titles related to Phd Math jobs in California? For Phd Math jobs in California, the most frequently searched job titles are:
What job categories do people searching Phd Math jobs in California look for? The top searched job categories for Phd Math jobs in California are:
What cities in California are hiring for Phd Math jobs? Cities in California with the most Phd Math job openings:
Phd Math jobs near you
Infographic showing various Phd Math job openings in California as of July 2026, with employment types broken down into 73% Full Time, 23% Part Time, 2% Temporary, 1% Contract, and 1% Nights. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $57,041 per year, or $27.4 per hour.
Senior Math Libraries Engineer - AI and HPC

Senior Math Libraries Engineer - AI and HPC

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 4 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

NVIDIA Math Libraries team is looking for a senior engineer to join our development efforts in the area of kernel generation for AI and HPC, specifically targeting matrix operations, JITing and fusions. Around the world, leading commercial and academic organizations are revolutionizing AI, scientific and engineering simulations, and data analytics, using data centers powered by GPUs. Applications of these technologies are in healthcare, NLP, VR, deep learning, autonomous vehicles and countless others. Did you know our team develops the GPU accelerated mathematical libraries that makes all of this possible?

What you will be doing:

  • Scoping, designing, and implementing high quality and performance numerical dense linear algebra software on GPUs.

  • Owning the execution of projects involving multiple engineers and sometimes teams.

  • Providing technical leadership and feedback to library engineers working with you on projects and sometimes mentor interns.

  • Working closely with product management and other internal and external customers to understand feature and performance requirements and contribute to the technical roadmaps of libraries.

  • Finding opportunities to improve library performance and reduce code maintenance overhead through re-architecting.

  • To be successful in your responsibilities which are by nature sophisticated, you will need to find and explain complex solutions, exercise leadership, and coordinate with multiple teams to work towards your goals.

What we need to see:

  • PhD, Master's, or Bachelor's degree in Computer Science, Applied Math, or related science or engineering field of study (or equivalent experience).

  • 8+ years of experience in designing, developing, testing, maintenance, and performance optimization of HPC software using C++.

  • Strong fundamentals in kernel generation and composable library design for linear algebra.

  • Leadership skills in driving software development projects.

  • Strong collaboration, communication, and documentation habits.

  • Kernel generation. JIT focus/experience desired

Ways to stand out from the crowd:

  • Experience with parallel programming, ideally using CUDA, MPI, OpenMP, OpenACC, pthreads.

  • Good understanding of Machine Learning and Deep Learning technologies as well as knowledge of GPU (preferred) or CPU hardware architecture.

  • Experience with low level programming using assembly for performance optimization and operator fusion is a huge plus.

  • Experience with agile software development practices using project management tools such as JIRA.

  • A scripting language, preferably Python.

With a competitive salary package and benefits, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous GenAI Engineer, who loves challenges? Do you have a genuine passion for advancing the state of AI & machine learning across a variety of industries? If so, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 12, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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