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Applied Math Jobs in Austin, TX (NOW HIRING)

Apple

Senior Manager - AI Data Operations

Austin, TX · On-site

Minimum Qualifications MS in Computer Science, Statistics, Applied Math or a related field 8+ years of people management of data scientists, statisticians, or other analysis-related teams. 10-12 ...

Applied Materials

Software Engineer II

Austin, TX · On-site

$108K - $148K/yr

Who We Are Applied Materials is a global leader in materials engineering solutions used to produce ... or mathematics * 2-4 years of related experience * Proficiency in C/C++, .Net, C#, Operating ...

Future Secure AI

Data Scientist, Applied Science

Austin, TX · On-site

$110K - $210K/yr

As an Applied Scientist, you will be a key contributor to the development and improvement of the AI ... Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field * Strong ...

BC Forward

Sourcing Manager IV (Engineering)

Austin, TX · On-site

$49 - $54/hr

Applied math skills for pricing, freight calculations, and label measurements. Bachelor's degree in Business Administration or related field, or equivalent combination of education and experience.

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All JobsApplied Math JobsApplied Math Jobs in Austin, TX

Applied Math information

See Austin, TX salary details

$22.3K

$58.3K

$93.7K

How much do applied math jobs pay per year?

As of Jul 9, 2026, the average yearly pay for applied math in Austin, TX is $58,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,600.00 and $69,400.00 per year, depending on experience, location, and employer.

What are the highest paying jobs in applied mathematics?

High-paying jobs in applied mathematics include roles such as quantitative analyst, data scientist, operations research analyst, and financial engineer, often requiring strong programming skills and advanced degrees. These positions typically offer salaries exceeding $100,000 annually, especially in finance, technology, and consulting industries.

Is applied math a useful degree?

Applied math is a useful degree for careers in data analysis, finance, engineering, and research, as it develops skills in problem-solving, modeling, and quantitative analysis. Graduates often work with tools like programming languages and statistical software, and the degree provides a strong foundation for various technical roles.

What jobs can you get with an applied maths degree?

Applied mathematics graduates can pursue roles such as data analyst, operations researcher, financial analyst, actuary, or software developer. These jobs often require strong analytical, problem-solving, and programming skills, and may involve working with statistical software or modeling tools in various industries like finance, technology, or healthcare.

What are applied math careers?

Applied math careers involve using mathematical methods and models to solve real-world problems across industries such as finance, engineering, data analysis, and technology. Professionals in this field often work with programming tools, statistical software, and data analysis techniques to develop solutions and support decision-making.

What are applied mathematicians?

Applied mathematicians are professionals who use mathematical theories, techniques, and computational methods to solve practical problems in fields such as engineering, science, business, and industry. They often develop models to analyze real-world phenomena, optimize processes, and predict outcomes. Applied mathematicians may work in diverse areas like data analysis, operations research, finance, and computer science, collaborating with experts from other disciplines to address complex challenges.

What is the difference between Applied Math vs Data Analyst?

AspectApplied MathData Analyst
Required CredentialsBachelor's or higher in Mathematics, Applied Math, or related fieldsBachelor's or higher in Statistics, Data Science, or related fields
Work EnvironmentResearch labs, academia, finance, engineeringBusiness, finance, healthcare, marketing
Industry UsageModeling, simulations, algorithm developmentData interpretation, reporting, visualization
Common Search/ComparisonApplied Math vs Data Analyst

Applied Math and Data Analysts often share skills in statistical analysis and problem-solving. However, Applied Math focuses more on developing mathematical models and algorithms, while Data Analysts primarily interpret and visualize data to inform business decisions. Both roles are vital across industries, but their daily tasks and focus areas differ significantly.

What are some typical projects or problems an applied mathematician may work on within a multidisciplinary team?

Applied mathematicians often collaborate with experts from fields such as engineering, computer science, and finance to tackle real-world challenges. For example, they might develop algorithms for optimizing logistics and supply chains, create mathematical models to predict disease spread in healthcare, or analyze large data sets to inform business strategies. This collaboration typically involves regular meetings, data sharing, and iterative problem solving, making strong communication skills and adaptability essential for success in the role.

What are the key skills and qualifications needed to thrive as an Applied Mathematician, and why are they important?

To thrive as an Applied Mathematician, you need strong mathematical modeling, analytical, and problem-solving skills, usually supported by a degree in mathematics, applied mathematics, or a related field. Familiarity with programming languages (such as Python, MATLAB, or R), statistical software, and computational tools is typically required. Excellent communication, teamwork, and critical thinking abilities help translate complex mathematical concepts for diverse audiences and collaborative projects. These skills are vital for developing solutions to real-world problems across industries, ensuring accuracy, innovation, and practical impact.
What are popular job titles related to Applied Math jobs in Austin, TX? For Applied Math jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Applied Math jobs in Austin, TX look for? The top searched job categories for Applied Math jobs in Austin, TX are:
What cities near Austin, TX are hiring for Applied Math jobs? Cities near Austin, TX with the most Applied Math job openings:
Applied Math jobs near you
Infographic showing various Applied Math job openings in Austin, TX as of July 2026, with employment types broken down into 73% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $58,320 per year, or $28 per hour.

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • Remote

Full-time

Re-posted 23 days ago

Job description

(Fully-remote US position)
About LiftLab

Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.

Job responsibilities

  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform

  • Performs diagnostics and root-cause analysis and provide fixes

  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow

Course work/experience:

  • Data manipulation

    • SQL

    • Operating on big datasets in Python

    • Data visualization

  • Mathematical optimization

    • Linear optimization concepts

    • Nonlinear continuous optimization

    • Linear algebra

  • Mathematical modeling

    • Using parametrized systems of equations to represent real-world systems

  • Statistics

    • Multivariate regression

    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters

    • Bayesian concepts

    • Hypotheses testing

Education requirements

Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience

Skills/Aptitude

  • Engineering and detective mindset

    • Both to diagnose data and existing algorithms and to develop new analytics functionality

  • Pragmatic approach to real-world problems

  • Focus on problem solving over applying specific models

  • Willingness to make approximations and assumptions rather than find "the" optimal solution

  • Ability to combine multiple techniques and models to solve end-to end-problems

  • Communication and collaboration skill

  • Ability to convert non-technical requests into project specifications

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