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Math Engineering Jobs in Kansas (NOW HIRING)

As required, work directly with Machine Shop, Inspection, Engineering, Planning to address concerns ... Strong mathematical skills. * Able to read instrumentation and gauges for measurement purposes.

Programmer

Wichita, KS · On-site

$18 - $40/hr

As required, work directly with Machine Shop, Inspection, Engineering, Planning to address concerns ... Strong mathematical skills. * Able to read instrumentation and gauges for measurement purposes.

Calculus 3 Tutor

Wichita, KS · Remote

$18 - $40/hr

Adapts instruction using 3D graphing software, step-by-step parametrization guidance, and engineering-focused problems for STEM majors and advanced mathematics students. * Effective Teaching Methods:

Calculus 3 Tutor

Overland Park, KS · Remote

$18 - $40/hr

Adapts instruction using 3D graphing software, step-by-step parametrization guidance, and engineering-focused problems for STEM majors and advanced mathematics students. * Effective Teaching Methods:

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Math Engineering information

See Kansas salary details

$20.1K

$52.5K

$84.3K

How much do math engineering jobs pay per year?

As of Jul 16, 2026, the average yearly pay for math engineering in Kansas is $52,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,100.00 and $62,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Math Engineer, and why are they important?

To thrive as a Math Engineer, you need a strong background in applied mathematics, computational methods, and a relevant engineering discipline, usually supported by a degree in mathematics, engineering, or a related field. Proficiency in programming languages (such as MATLAB, Python, or C++), mathematical modeling software, and familiarity with simulation tools are typically required. Analytical thinking, problem-solving abilities, and effective communication skills are essential soft skills to excel in this role. These skills and qualities are crucial for accurately modeling complex systems, developing innovative solutions, and effectively collaborating with multidisciplinary teams.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High-level roles often require advanced degrees, certifications, and expertise in high-demand areas or management positions within large organizations.

What is the difference between Math Engineering vs Data Scientist?

AspectMath EngineeringData Scientist
Required CredentialsMathematics, Engineering, Computer Science degreesStatistics, Computer Science, Mathematics degrees
Work EnvironmentResearch labs, R&D departments, technical teamsBusiness settings, analytics teams, tech companies
Employer & Industry UsageTech firms, engineering companies, financeTech, finance, healthcare, marketing
Common Search & ComparisonMath Engineering vs Data Scientist

Math Engineering focuses on applying advanced mathematical techniques to develop engineering solutions, often in R&D or technical roles. Data Scientists analyze large datasets to extract insights, primarily supporting business decisions. While both roles require strong math skills, Math Engineering emphasizes engineering applications, whereas Data Science centers on data analysis and modeling.

What does a math engineer do?

A math engineer applies mathematical principles and techniques to solve complex problems in engineering, technology, and scientific fields. They develop models, algorithms, and simulations, often using programming tools like MATLAB or Python, to optimize systems and processes. Their work supports innovation in areas such as data analysis, machine learning, and product design.

What engineers make $500,000?

Senior engineers in fields such as software, petroleum, aerospace, and electrical engineering can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High-level roles typically require extensive experience, advanced skills, and sometimes leadership responsibilities or specialized certifications.

How does a Math Engineer typically collaborate with software developers and data scientists on interdisciplinary projects?

Math Engineers often work closely with software developers and data scientists to design and implement mathematical models and algorithms. Collaboration involves translating complex mathematical concepts into practical computational solutions, validating results, and optimizing performance. Regular meetings, code reviews, and shared documentation help ensure alignment across teams, and strong communication skills are essential for explaining technical details to non-specialists. This interdisciplinary teamwork is common in industries like finance, technology, and engineering, leading to innovative solutions and continuous learning opportunities.

What engineering jobs use math?

Math engineering jobs include roles such as aerospace, civil, electrical, and mechanical engineers, all of which rely heavily on advanced mathematics for design, analysis, and problem-solving. These positions often require skills in calculus, linear algebra, and differential equations, and may involve using tools like MATLAB or CAD software.

What is math engineering?

Math engineering is a multidisciplinary field that applies advanced mathematical theories, techniques, and computational methods to solve engineering problems. Professionals in this area use mathematics to model, analyze, and optimize systems in industries such as technology, finance, aerospace, and manufacturing. Typical tasks include developing algorithms, performing simulations, and interpreting complex data to improve processes or products. Math engineers often work closely with other engineers and scientists to design efficient solutions to real-world challenges.
What are popular job titles related to Math Engineering jobs in Kansas? For Math Engineering jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Math Engineering jobs in Kansas look for? The top searched job categories for Math Engineering jobs in Kansas are:
Infographic showing various Math Engineering job openings in Kansas as of July 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $52,474 per year, or $25.2 per hour.
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Topeka, KS

$74K/yr

Other

Posted 7 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

238th of 693 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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