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Phd Math Jobs in California (NOW HIRING)

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How much do phd math jobs pay per hour?

As of Aug 22, 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 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 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.

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 tend to earn higher salaries, often exceeding $100,000 annually, especially with experience and specialized skills. However, academic positions may offer lower pay compared to private sector roles.

Is a PhD in math useful?

A PhD in math is highly valuable for careers in academia, research, data science, and quantitative analysis, where advanced analytical and problem-solving skills are essential. It can also open opportunities in industry sectors such as finance, technology, and engineering, often requiring expertise in mathematical modeling and programming tools like MATLAB or Python.

What is the salary of a PhD in math?

A PhD in math typically earns between $70,000 and $120,000 annually, depending on the industry, location, and experience. Academic positions such as university professors may have lower starting salaries but offer research and teaching opportunities, while industry roles in finance, data science, or technology tend to offer higher compensation.

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 August 2026, with employment types broken down into 78% Full Time, 19% Part Time, 1% 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 - Sparse Linear Algebra

Nvidia Corporation

Santa Clara, CA • On-site

$55K - $72K/yr

Full-time

Re-posted 16 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

We are looking for software engineers to join our development efforts in the area of sparse linear algebra kernels for high-performance libraries such as cuSPARSE and cuDSS. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high-performance linear algebra libraries. Applications of these technologies include computer aided engineering (CAE), electronic design automation (EDA), quantum chemistry, autonomous vehicles, LLMs, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible?
In this role, you will work together with other developers on designing, developing, and optimizing kernels for various algorithms including basic sparse BLAS operations like matrix-vector-products and matrix-matrix-products, direct sparse solvers, iterative sparse solvers, preconditioners, and algebraic multigrid (AMG). Ideal candidates will not only have experience developing accelerated computing kernels, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains. If this sounds exciting, we would love to meet you!
What you will be doing:
  • Designing, implementing and optimizing scalable high-performance numerical sparse linear algebra software for existing and future GPU architectures
  • Working with library engineers, QA engineers, and interns on topics ranging from sparse BLAS operations to advanced direct and iterative sparse solvers
  • Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries
  • Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices

What we need to see:
  • PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field is preferred
  • 5+ years of overall experience in developing, debugging and optimizing high-performance sparse linear algebra software using C++ and parallel programming; ideally using CUDA, MPI, OpenMP, OpenACC, pthreads, or equivalent technologies
  • Strong fundamentals in floating point arithmetic and implementation of sparse linear algebra primitives like matrix-vector and matrix-matrix products
  • Experience in developing , maintaining, and testing sparse linear algebra libraries
  • Strong collaboration, communication, and documentation habits.

Ways to stand out from the crowd:
  • Good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization
  • Familiarity with technologies such as multi-frontal factorizations, iterative solvers, preconditioners, and algebraic multigrid
  • Experience with adopting and advancing software development practices such as CI/CD systems and project management tools such as JIRA
  • Understanding of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)
  • Working experience in a globally distributed and agile organization

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative, autonomous and love a challenge, 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 152,000 USD - 218,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until January 13, 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

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Benefits

Hours and flexibility

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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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