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Internship Data Science Economics Jobs in Wisconsin

You will work on a skilled team of passionate data scientists and meteorologists. Examples of ... MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series ...

You will work on a skilled team of passionate data scientists and meteorologists. Examples of ... MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series ...

$22 - $24/hr

Majors: Accounting, Finance, Business Administration, Economics, Business Analytics, Statistics ... Data Science or Management Information Systems preferred * Education: Current undergraduate student ...

$22 - $24/hr

Majors: Accounting, Finance, Business Administration, Economics, Business Analytics, Statistics ... Data Science or Management Information Systems preferred * Education: Current undergraduate student ...

$22 - $24/hr

Majors: Accounting, Finance, Business Administration, Economics, Business Analytics, Statistics ... Data Science or Management Information Systems preferred * Education: Current undergraduate student ...

Showing results 41-60

Internship Data Science Economics information

What is an internship in data science economics?

An Internship in Data Science Economics is a temporary position that allows students or recent graduates to gain practical experience applying data science techniques to economic problems. Interns typically work on projects involving data analysis, statistical modeling, and economic research, often using programming languages like Python or R. The role helps bridge the gap between academic knowledge and real-world applications, providing valuable skills for a future career in data science or economics.

What types of projects do interns typically work on in a data science economics internship?

Interns in Data Science Economics roles often work on projects involving data analysis, economic modeling, and statistical research to support business decision-making. These projects may include analyzing large datasets to identify economic trends, building predictive models, and creating visualizations to communicate insights. Interns usually collaborate closely with both data scientists and economists, gaining exposure to real-world applications of economic theories and data-driven problem-solving. This hands-on experience helps interns develop technical and analytical skills while contributing meaningful work to the team.

What are the key skills and qualifications needed to thrive as an internship data science economics, and why are they important?

To thrive as an Internship Data Science Economics, you need a solid background in statistics, econometrics, and programming languages like Python or R, typically supported by progress toward a degree in economics, data science, or a related field. Familiarity with data analysis tools such as SQL, statistical software, and visualization platforms like Tableau is often required. Strong analytical thinking, effective communication, and the ability to collaborate in team environments help interns excel in this role. These skills are crucial for interpreting economic data, delivering actionable insights, and supporting informed decision-making within organizations.

What is the difference between Internship Data Science Economics vs Data Analyst Intern?

AspectInternship Data Science EconomicsData Analyst Intern
Required SkillsStatistics, economics, programming (Python/R), data analysisData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, economic modeling, data interpretationBusiness insights, reporting, dashboard creation
Industry UsageFinance, consulting, government, research institutionsMarketing, finance, tech companies

Internship Data Science Economics typically involves economic modeling, statistical analysis, and programming skills, often in research or policy environments. Data Analyst Internships focus on interpreting data to generate business insights, using tools like Excel and SQL. Both roles require analytical skills but differ in focus and industry applications.

What are popular job titles related to Internship Data Science Economics jobs in Wisconsin?

For Internship Data Science Economics jobs in Wisconsin, the most frequently searched job titles are:

What cities in Wisconsin are hiring for Internship Data Science Economics jobs?

Cities in Wisconsin with the most Internship Data Science Economics job openings:

Infographic showing various Internship Data Science Economics job openings in Wisconsin as of August 2026, with employment types broken down into 6% Internship, 57% Full Time, 29% Part Time, 6% Temporary, and 2% Contract. Highlights an 86% In-person, 12% Hybrid, and 2% Remote job distribution.

Data Scientist (Statistician) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Green Bay, WI • On-site

$125K/yr

Full-time

Posted 5 days ago


Internal Revenue Service rating

7.5

Company rating: 7.5 out of 10

Based on 129 frontline employees who took The Breakroom Quiz

130th of 294 rated public sector bodies


Job description

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

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications: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 closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:
  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

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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