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Statistical Data Jobs in Wisconsin (NOW HIRING)

Bachelor's degree in Statistics, Data Science, Computer Science, Operations Research or a related field and 4 years in any job title involving statistical and machine learning modeling experience.

The Maintenance Technician will perform machine calibrations, compile and analyze statistical data for critical equipment, and assist with machine optimization as needed. Responsibilities * Support ...

The Maintenance Technician will perform machine calibrations, compile and analyze statistical data for critical equipment, and assist with machine optimization as needed. Responsibilities * Support ...

The Maintenance Technician will perform machine calibrations, compile and analyze statistical data for critical equipment, and assist with machine optimization as needed. Responsibilities * Support ...

The Maintenance Technician will perform machine calibrations, compile and analyze statistical data for critical equipment, and assist with machine optimization as needed. Responsibilities * Support ...

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Statistical Data information

Is statistician a high paying job?

Statisticians typically earn higher-than-average salaries compared to many other professions, especially with advanced degrees and experience. The median annual wage in many regions exceeds national averages, and roles often require strong analytical skills and proficiency with statistical software. Salary levels can vary based on industry, location, and level of expertise.

What are the key skills and qualifications needed to thrive as a Statistical Data Analyst, and why are they important?

To thrive as a Statistical Data Analyst, you need strong quantitative skills, expertise in statistics, and a relevant degree such as mathematics, statistics, or data science. Proficiency with tools like R, Python, SQL, and statistical software (e.g., SPSS, SAS) as well as data visualization platforms is typically required. Critical thinking, attention to detail, and effective communication skills help analysts interpret data accurately and share insights with stakeholders. These competencies ensure reliable data analysis, support evidence-based decisions, and drive organizational success.

What are some common challenges faced by professionals working in statistical data roles, and how can they be addressed?

Professionals in statistical data roles often encounter challenges such as managing large, complex datasets, ensuring data quality, and effectively communicating statistical findings to non-technical stakeholders. Dealing with incomplete or inconsistent data is common, and requires strong analytical and problem-solving skills to clean and validate information. Collaborating closely with cross-functional teams, staying updated on the latest statistical software, and developing clear data visualization skills can help address these challenges and enhance the impact of your work.

What careers deal with statistics?

Careers that deal with statistics include roles such as statistician, data analyst, data scientist, biostatistician, and market researcher. These jobs involve analyzing data, creating models, and interpreting results using tools like statistical software and programming languages such as R or Python.

Is AI replacing statisticians?

AI is transforming the role of statisticians by automating data analysis tasks and enabling more complex modeling, but it does not fully replace the need for human expertise in interpreting results and designing studies. Statisticians with skills in programming, statistical software, and machine learning remain essential for ensuring accurate and meaningful insights from data. The profession continues to evolve alongside advancements in AI and data science tools.

What is the difference between Statistical Data vs Data Analyst?

AspectStatistical DataData Analyst
Required CredentialsNone specific; often involves understanding data collectionBachelor's degree in statistics, data science, or related field
Work EnvironmentData collection, storage, and management environmentsAnalyzing data, creating reports, and visualizations
Industry UsageUsed across industries for data collection and storageApplied in business, finance, healthcare, and more for insights
Search & Comparison IntentUnderstanding raw data types and sourcesComparing roles focused on data analysis and interpretation

Statistical Data refers to raw or processed data used for analysis, while Data Analyst is a professional role that interprets and visualizes this data to support decision-making. Both are integral to data-driven industries but serve different functions within the data lifecycle.

What are statistical data analysts?

Statistical data analysts are professionals who collect, process, and interpret quantitative data to help organizations make informed decisions. They use statistical techniques and software tools to analyze datasets, identify trends, and solve problems. Their work is crucial in fields such as business, healthcare, government, and research, where data-driven insights are essential. Statistical data analysts often present their findings in reports or visualizations to guide strategic planning.

What does a data statistician do?

A data statistician analyzes and interprets complex data sets to help organizations make informed decisions. They design experiments, develop statistical models, and use tools like R or SAS to identify trends and patterns, often working in research, finance, or healthcare environments.
What are popular job titles related to Statistical Data jobs in Wisconsin? For Statistical Data jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Statistical Data jobs? Cities in Wisconsin with the most Statistical Data job openings:
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Madison, WI

$74K/yr

Other

Posted 5 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

235th of 692 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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