1

Data Analytics Graduate Jobs in Wisconsin (NOW HIRING)

Ability to be proficient in data analytics programs, systems, and databases to identify risks and ... Graduate of a Medical Coding Program * Two years of Coding experience may be considered in lieu of ...

Ability to be proficient in data analytics programs, systems, and databases to identify risks and ... Graduate of a Medical Coding Program * Two years of Coding experience may be considered in lieu of ...

Power BI Intern

Green Bay, WI · On-site

$15/hr

Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics, Information Systems, Business, or related field. * Basic experience or coursework with Power BI, including ...

Power BI Intern

Milwaukee, WI · On-site

$15/hr

Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics, Information Systems, Business, or related field. * Basic experience or coursework with Power BI, including ...

Power BI Intern

Menomonie, WI · On-site

$15/hr

Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics, Information Systems, Business, or related field. * Basic experience or coursework with Power BI, including ...

$15/hr

Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics, Information Systems, Business, or related field. * Basic experience or coursework with Power BI, including ...

next page

Showing results 1-20

Data Analytics Graduate information

See Wisconsin salary details

$24

$55

$95

How much do data analytics graduate jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for data analytics graduate in Wisconsin is $55.26, according to ZipRecruiter salary data. Most workers in this role earn between $44.42 and $62.60 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Analytics Graduate position, and why are they important?

To thrive as a Data Analytics Graduate, you need a solid understanding of statistics, data modeling, and analytical techniques, usually supported by a relevant degree in mathematics, statistics, computer science, or a related field. Familiarity with tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is highly valued, and certifications in these can provide an added advantage. Strong problem-solving abilities, attention to detail, and effective communication skills help you distill complex data sets into actionable insights and present findings to diverse stakeholders. These skills are essential for delivering data-driven solutions that support business decisions and foster organizational growth.

What are typical career paths or growth opportunities for a Data Analytics Graduate?

As a Data Analytics Graduate, you often start by supporting more senior analysts with data preparation, exploratory analysis, and report generation. Over time, you can advance to positions such as Data Analyst, Business Intelligence Analyst, or Data Scientist, depending on your interests and ongoing skill development. Many organizations encourage further training and offer mentorship to help you specialize in areas like machine learning, data engineering, or domain-focused analytics. With experience and demonstrated impact, leadership roles such as Analytics Manager or Team Lead become attainable, providing broader responsibilities and strategic input into organizational decision-making.

What is a Data Analytics Graduate job?

A Data Analytics Graduate job is an entry-level role designed for recent graduates with a background in data science, statistics, or related fields. It typically involves collecting, cleaning, analyzing, and visualizing data to help organizations make data-driven decisions. Graduates in this role may work with tools like SQL, Python, Excel, and data visualization software to interpret trends and patterns. They often collaborate with different departments to provide insights that optimize business processes. This role serves as a foundation for more advanced positions in data analytics or data science.

What are the most commonly searched types of Data Analytics Graduate jobs in Wisconsin? The most popular types of Data Analytics Graduate jobs in Wisconsin are:
What are popular job titles related to Data Analytics Graduate jobs in Wisconsin? For Data Analytics Graduate jobs in Wisconsin, the most frequently searched job titles are:
Infographic showing various Data Analytics Graduate job openings in Wisconsin as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 6% Part Time, 1% Temporary, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $114,938 per year, or $55.3 per hour.

Mathematical Statistician (Data Scientist) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Green Bay, WI

$74K/yr

Other

Posted 10 days ago


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