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Remote Applied Mathematics Jobs in Austin, TX (NOW HIRING)

SpyCloud

Senior Data Scientist, Applied ML

Austin, TX · On-site +1

$154K - $200K/yr

Strong background in applied math (linear algebra, optimization, statistics) and machine learning ... In addition to our engaging workspace in South Austin, flexible and remote-friendly work options ...

Dlapiper

Data Scientist

Austin, TX · On-site +1

Bachelor's degree in computer science, data science, statistics, applied mathematics or related ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

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All JobsApplied Mathematics JobsRemote Applied Mathematics JobsRemote Applied Mathematics Jobs in Austin, TX

Remote Applied Mathematics information

See Austin, TX salary details

$20.1K

$75.9K

$182K

How much do remote applied mathematics jobs pay per year?

As of Aug 20, 2026, the average yearly pay for remote applied mathematics in Austin, TX is $75,914.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,738.00 and $97,628.00 per year, depending on experience, location, and employer.

What is a remote applied mathematics?

A Remote Applied Mathematics job involves using mathematical theories and techniques to solve real-world problems in various industries while working from a remote location. Professionals in this field apply mathematical modeling, statistical analysis, and computational methods to fields like finance, engineering, data science, and operations research. They often collaborate with teams virtually, using digital tools to analyze data, develop algorithms, and optimize solutions. Strong problem-solving skills and proficiency in programming languages like Python, R, or MATLAB are commonly required. This role offers flexibility and allows mathematicians to contribute to diverse industries without being tied to a physical office.

What are some typical projects or problems addressed by professionals in remote applied mathematics roles?

Professionals in Remote Applied Mathematics frequently tackle complex problems such as optimizing processes, developing statistical models, or analyzing large datasets to extract actionable insights for industries like finance, healthcare, or engineering. Their daily work often involves collaborating with multidisciplinary teams via virtual meetings, sharing research findings, and validating results through computational simulations or data analysis. Project scopes can range from short-term consultations to long-term research, allowing for significant variety and intellectual engagement. This dynamic environment enables applied mathematicians to make real-world impacts while building a versatile skill set relevant to a variety of sectors.

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

To thrive in Remote Applied Mathematics, you need a solid background in mathematical modeling, statistical analysis, and problem-solving, usually substantiated by a degree in mathematics, applied math, or a related field. Familiarity with programming languages such as Python, MATLAB, or R, and experience using data analysis software is highly valued. Strong communication, self-motivation, and time management skills help remote professionals collaborate and meet project goals effectively. These combined abilities are crucial to deliver high-quality mathematical solutions and insights while working independently in a virtual environment.

Can applied mathematicians work remotely?

Applied mathematicians can often work remotely, especially in roles involving data analysis, modeling, or software development, which primarily require a computer and internet connection. Many employers offer remote or hybrid arrangements, and skills in programming and statistical tools facilitate remote work environments.

Is applied mathematics in demand?

Applied mathematics is in high demand across industries such as finance, engineering, data science, and technology, where analytical and problem-solving skills are essential. Professionals with expertise in mathematical modeling, programming, and statistical analysis are sought after for roles in research, development, and data-driven decision making.

What jobs can I do with a remote applied mathematics degree?

A remote applied mathematics degree qualifies you for roles such as data analyst, quantitative analyst, operations researcher, or mathematical modeler. These jobs often require skills in programming, statistical software, and problem-solving, and may involve working with data, algorithms, or simulations in various industries like finance, technology, or research.

What jobs can you get with a remote applied mathematics degree?

A remote applied mathematics degree can lead to roles such as data analyst, quantitative analyst, operations researcher, or software developer. These positions often require strong analytical skills, proficiency in programming languages like Python or R, and the ability to work independently in a virtual environment.

What are the most commonly searched types of Applied Mathematics jobs in Austin, TX?

The most popular types of Applied Mathematics jobs in Austin, TX are:

What are popular job titles related to Remote Applied Mathematics jobs in Austin, TX?

For Remote Applied Mathematics jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Remote Applied Mathematics jobs in Austin, TX look for?

The top searched job categories for Remote Applied Mathematics jobs in Austin, TX are:

What cities near Austin, TX are hiring for Remote Applied Mathematics jobs?

Cities near Austin, TX with the most Remote Applied Mathematics job openings:

Remote Applied Mathematics jobs near you
Infographic showing various Remote Applied Mathematics job openings in Austin, TX as of August 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 13% In-person, and 87% Remote job distribution, with an average salary of $75,914 per year, or $36.5 per hour.

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • Remote

Full-time

Re-posted 5 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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