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Mathematics Phd Jobs in Texas (NOW HIRING)

Citadel

$4.5K - $5.8K/wk

PhD degree in computer science, mathematics, statistics, physics, or another highly quantitative field * Strong programming skills with proficiency in one or more programming languages, including C ...

Citadel

$4.5K - $5.8K/wk

PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field * Advanced training and a strong research track record in machine learning, statistics, deep ...

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Mathematics Phd information

See Texas salary details

$19.6K

$48.9K

$93.6K

How much do mathematics phd jobs pay per year?

As of Sep 8, 2026, the average yearly pay for mathematics phd in Texas is $48,894.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,100.00 and $52,200.00 per year, depending on experience, location, and employer.

What is a mathematics PhD?

A Mathematics PhD job typically involves advanced research, teaching, and applying mathematical theories in academia, industry, or government. Mathematicians with a PhD may work as professors, researchers, data scientists, or analysts, solving complex problems in fields such as finance, engineering, and technology. Their roles often require deep theoretical knowledge, programming skills, and collaboration with experts from other disciplines.

What are typical career paths and advancement opportunities for someone with a mathematics PhD?

With a Mathematics PhD, professionals often pursue careers in academia as professors or researchers, as well as in industry roles such as data scientist, quantitative analyst, or applied mathematician. Advancement can involve moving from postdoctoral positions to tenure-track faculty, or progressing to senior research, technical lead, or management roles in private sector organizations. Many organizations value the ability to lead interdisciplinary projects and contribute original research, offering opportunities for publishing, speaking at conferences, and acquiring grants or patents. Career growth typically comes from building a strong research portfolio, developing specialized expertise, and demonstrating the ability to solve complex, high-impact problems. Collaborating across departments and industries can further broaden your career prospects and open doors to leadership positions.

What are the key skills and qualifications needed to thrive in the mathematics PhD position, and why are they important?

To thrive as a Mathematics PhD, you need deep expertise in advanced mathematics and statistical theory, typically demonstrated by an earned doctoral degree. Familiarity with computational tools such as MATLAB, R, Python, and mathematical modeling software is often required. Strong analytical thinking, creativity in problem-solving, and effective communication skills are highly valued. These abilities are crucial for producing original research, collaborating with interdisciplinary teams, and applying complex mathematical concepts to solve real-world problems.

Are mathematics PhDs in demand?

Mathematics PhDs are in demand in fields such as academia, data science, finance, and research, where advanced analytical and problem-solving skills are valued. Employment opportunities often require strong quantitative skills, programming knowledge, and research experience, with demand driven by data-driven decision making and technological advancements.

How much do mathematics PhDs make?

Mathematics PhDs typically earn between $70,000 and $120,000 annually, depending on the industry, experience, and location. Academic positions often start lower but can increase with tenure and research funding, while industry roles in finance, technology, or data science tend to offer higher salaries and additional benefits.

Is a mathematics PhD worth it?

A mathematics PhD can lead to careers in academia, research, data analysis, and quantitative roles, often requiring strong analytical and problem-solving skills. While it offers advanced expertise, the investment in time and cost varies, and job prospects depend on specialization and industry demand.

What jobs can I get with a PhD in Mathematics?

A PhD in Mathematics qualifies individuals for roles such as research mathematician, data scientist, quantitative analyst, operations researcher, or university professor. These positions often require strong analytical, problem-solving, and programming skills, and may involve working in academia, finance, technology, or government agencies.

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

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

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

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

What cities in Texas are hiring for Mathematics Phd jobs?

Cities in Texas with the most Mathematics Phd job openings:

Mathematics Phd jobs near you
Infographic showing various Mathematics Phd job openings in Texas as of September 2026, with employment types broken down into 1% Internship, 80% Full Time, 11% Part Time, 2% Temporary, 5% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $48,894 per year, or $23.5 per hour.

Quantitative Research Intern, PhD (Summer 2027)

Optiver

Austin, TX • On-site

Other

Re-posted 8 days ago

Job description

As a Quantitative Research Intern, you'll work alongside researchers, engineers, and traders to tackle some of the most challenging quantitative problems in global financial markets. You'll analyze large-scale datasets, develop predictive models and algorithms, and apply statistical and machine learning techniques to uncover patterns in market behavior. AI-driven research at Optiver is where competitive advantage is built, transforming ideas, models, and insights into trading strategies that operate in live markets.
This opportunity is also available in our Chicago office.
What You'll Do:
Led by our dedicated Education team, you'll build a strong foundation in market structure and options theory. This internship follows an apprentice-style learning model where you'll work alongside an experienced researcher and contribute to a project that's aligned with current business needs. Throughout the internship, you'll gain exposure to the AI tools and technologies that support research and development across the business, with the opportunity to contribute to several key areas:

  • Develop predictive models and machine learning systems to better understand market behavior and identify trading opportunities
  • Analyze large-scale market and order-flow data to uncover signals, evaluate hypotheses, and improve trading performance
  • Build and test statistical and stochastic models for pricing, forecasting, and risk management
  • Apply modern research techniques, including deep learning and AI-enabled workflows, to accelerate discovery and improve research efficiency
What You'll Get:
You'll join a culture of collaboration, continuous improvement, and excellence, surrounded by curious thinkers and creative problem-solvers. Together, you'll tackle some of the toughest challenges in the financial markets by leveraging cutting-edge machine learning research to develop innovative, real-world solutions.
In addition, you'll receive:
  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • The opportunity to earn a return internship or full-time offer in Chicago, Austin, or New York City based on performance
  • A highly-competitive internship compensation package
  • Optiver-covered flights, living accommodations, and commuting stipends
  • Extensive office perks, including breakfast, lunch, snacks, regular social events, clubs, sporting leagues, and more
What To Expect:
As part of our assessment process, you may be invited to participate in a multi-day, on-site evaluative program. Through hands-on workshops, technical discussions, and direct exposure to our researchers and traders, you'll gain insight into how research is applied at Optiver and how PhD students transition successfully into industry. Attendance and successful completion of this program may be required to receive an internship offer.
Who You Are:
  • Currently enrolled in a PhD program in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field with outstanding academic performance
  • Expected graduation between December 2027 - June 2029 and available to intern during Summer 2027
  • Open to full-time opportunities upon graduation in 2028 or 2029
  • Solid foundation in mathematics, probability, and statistics
  • Excellent research, analytical, and modeling skills
  • Experience applying machine learning methods to real-world research problems, such as time-series analysis, prediction, forecasting, pattern recognition, optimization, or decision-making
  • Proficiency in any programming language
  • Strong interest in working in a fast-paced, collaborative environment
  • Fluent in English with strong written and verbal communication skills

Who We Are:
Optiver is a leading technology- and research-driven trading firm. Our teams of scientists, engineers, mathematicians, and traders work side by side to develop, test, and scale ideas that shape how we understand and trade global markets. Powered by a global platform built for rapid experimentation and iteration, we combine the scientific rigor of a research institution with the pace of a technology company.
Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
Optiver is supportive of US immigration sponsorship for this role.
*Optiver has a global application re-apply policy for our intern and graduate roles. If you have completed an online assessment or interviewed for a quantitative graduate or internship role at any Optiver location in the past 8 months, please note that you are not yet eligible to reapply. We welcome you to re-apply to after the 8-month cool off period.

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