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Applied Statistics Jobs in Wisconsin (NOW HIRING)

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Applied Statistics information

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$40.9K

$84.4K

$118.1K

How much do applied statistics jobs pay per year?

As of Jul 19, 2026, the average yearly pay for applied statistics in Wisconsin is $84,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $117,100.00 per year, depending on experience, location, and employer.

Is AI replacing statisticians?

Applied statisticians use data analysis, modeling, and statistical tools to interpret data and inform decisions. AI can automate routine tasks and enhance data processing, but statisticians are needed to design experiments, validate models, and interpret complex results, making their role complementary rather than replaceable by AI.

What are typical projects or responsibilities for professionals in Applied Statistics?

Professionals in Applied Statistics can expect to work on projects involving data collection, cleaning, statistical modeling, and interpretation of results for practical applications in fields like healthcare, finance, marketing, or engineering. Daily responsibilities may include designing experiments or surveys, performing hypothesis testing, and creating actionable reports or presentations for non-technical audiences. Collaboration with multidisciplinary teams—such as data scientists, subject matter experts, and business leaders—is common to ensure data-driven solutions align with organizational goals. This diversity of tasks provides valuable learning experiences and opportunities for career growth into roles such as senior analyst, data scientist, or statistical consultant.

What do you do with an applied statistics degree?

An applied statistics degree prepares individuals for roles such as data analyst, statistician, or data scientist, involving data collection, analysis, and interpretation to support decision-making. Professionals often use tools like R, Python, or SAS and may work in industries such as healthcare, finance, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is an Applied Statistics job?

An Applied Statistics job involves using statistical methods and data analysis techniques to solve real-world problems across various industries. Professionals in this field apply mathematical models, statistical software, and analytical reasoning to interpret data, make informed decisions, and optimize processes. They often work in sectors like healthcare, finance, marketing, and technology, providing insights and recommendations based on data trends.

What does applied statistics do?

Applied statistics involves using statistical methods and data analysis techniques to solve real-world problems across various industries. Professionals in this field collect, interpret, and present data to support decision-making, often utilizing tools like statistical software and programming languages such as R or Python.

Is applied statistics a good career?

Applied statistics is a strong career choice for those interested in data analysis, modeling, and decision-making, often requiring skills in programming, statistical software, and critical thinking. Professionals in this field are in demand across industries such as healthcare, finance, and technology, with opportunities for advancement and specialization. The role typically involves working with large datasets and applying statistical methods to solve real-world problems.

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

To thrive in Applied Statistics, you need a solid background in statistical theory, data analysis, and mathematical modeling, typically with a degree in statistics, mathematics, or a related field. Familiarity with statistical software such as R, SAS, Python, or SPSS, and often certifications in analytics or data science, is important. Strong analytical thinking, effective communication, and problem-solving abilities help set candidates apart. These skills ensure accurate analysis of complex data, meaningful interpretation for stakeholders, and valuable contributions to evidence-based decision making.

What are popular job titles related to Applied Statistics jobs in Wisconsin? For Applied Statistics jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Applied Statistics jobs in Wisconsin look for? The top searched job categories for Applied Statistics jobs in Wisconsin are:
What cities in Wisconsin are hiring for Applied Statistics jobs? Cities in Wisconsin with the most Applied Statistics job openings:
Infographic showing various Applied Statistics job openings in Wisconsin as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, 2% Temporary, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $84,439 per year, or $40.6 per hour.
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

La Crosse, WI

$74K/yr

Other

Posted 10 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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