ZipRecruiter

Log In

1

Internship Data Science Economics Jobs in Wisconsin

Cliftonlarsonallen

Manager of Data Science

Hudson, WI · On-site

Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred. * Masters in a Data Science ...

Cliftonlarsonallen

Manager of Data Science

Racine, WI · On-site

Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred. * Masters in a Data Science ...

CliftonLarsonAllen

Manager of Data Science

Hudson, WI · On-site

Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred. * Masters in a Data Science ...

US Venture, Inc.

Data Science Intern

Appleton, WI · On-site

Venture Data and Analytics team as a Data Science Intern for Summer 2027! U.S ... Venture's Internship Program runs May - August 2027. Dates may vary based on individual class ...

next page

Showing results 1-20

All JobsData Science Economics JobsInternship Data Science Economics JobsInternship Data Science Economics Jobs in Wisconsin

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 job categories do people searching Internship Data Science Economics jobs in Wisconsin look for?

The top searched job categories for Internship Data Science Economics jobs in Wisconsin 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:

Internship Data Science Economics jobs near you
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.

Manager of Data Science

Cliftonlarsonallen

Hudson, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 13 days ago

CliftonLarsonAllen rating

7.0

Company rating: 7.0 out of 10

Based on 29 frontline employees who took The Breakroom Quiz

22nd of 23 rated bookkeepers and accountants

Job description

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is looking to hire a Data Science Director to join our growing Internal IT team.

About the role:

CLA is looking to hire a Manger of Data Science

This role constructs complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric algorithms in the process. This role will develop more autonomy to develop solutions and will lead others, take on administrative tasks, perform support roles, and get involved in new business development.

As Manager of Data Science, you will have to following responsibilities:

Leadership
  • Provide daytoday leadership, coaching, development, and performance management.
  • Mentor and guide analysts, supporting onboarding, skill development, and continuous learning across career stages.
  • Conduct workload planning, prioritization, and resource allocation to support multiple concurrent initiatives.
  • Build and sustain a highperforming team culture rooted in collaboration, quality, accountability, and innovation.

Technical Oversight

  • Lead and oversee large scale analytical and AI initiatives, including data acquisition, transformation, modeling, AI system development, automation, and insight generation.
  • Provide technical oversight and review of analytical approaches, models, and AI systems to ensure sound methodology, reproducibility, and scientific rigor.
  • Guide the development and application of advanced statistical, machine learning, and AI-driven solutions, including predictive models, computer vision, large language models (LLMs), and agent-based systems.
  • Lead the design and oversight of AI-enabled systems, including prompt engineering strategies, retrieval-augmented generation (RAG), embeddings, and agentic workflows.
  • Establish and evolve analytical and AI best practices, documentation standards, and technical frameworks across the team.
  • Ensure standards for model and AI system validation, monitoring, evaluation, documentation, and responsible AI use are consistently applied.
  • Partner with engineering, IT, and data platform teams to enable scalable, reliable, and well governed solutions.

Workflow Management

  • Own delivery outcomes for data science and AI workstreams, ensuring solutions meet quality, performance, and business expectations.
  • Translate business objectives into clear analytical and AI priorities, balancing near term delivery with long term capability building.
  • Oversee planning, prioritization, and resourcing across projects and teams.
  • Monitor solution performance, validation results, and model or AI system stability; guide troubleshooting of complex data, model, or AI issues.
  • Ensure solutions are productionized effectively, with clear ownership, monitoring, and integration into business workflows.
  • Establish, refine, and enforce standards for documentation, reproducibility, quality assurance, and governance.
  • Remove obstacles, manage risks, and ensure consistent execution across initiatives.

CrossFunctional Collaboration

  • Serve as a primary point of contact for business and functional leaders on analytics and AI initiatives.
  • Partner with stakeholders to define business questions, success metrics, analytical frameworks, and delivery expectations.
  • Coordinate work across teams, offices, and disciplines to ensure alignment of analytical and AI approaches and outcomes.
  • Communicate progress, risks, and results clearly to both technical and non technical audiences.
  • Evaluate and recommend adoption of new data sources, technologies, and analytical and AI tools.
  • Contribute to enterprise level analytics and AI strategy, including identifying high impact use cases and guiding their transition from concept to production.

What you will need:

8 years of relevant experience required.

  • Experience in data analytics, statistics, data science, AI, financial consulting, computer science or related field required.
  • Experience with APIs, web scraping, SQL/no-SQL databases, and cloud-based data solutions required.
  • Supervisory experience required.

Education

Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.

  • Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred.
  • Masters in a Data Science/Analytics/AI is a plus

#LI-JH1


Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
Click here to learn about your hiring rights.


Wellness at CLA

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.


To view a complete list of benefits, click here.


What CliftonLarsonAllen employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

CliftonLarsonAllen logo

About CliftonLarsonAllen

Sourced by ZipRecruiter

CliftonLarsonAllen (CLA) is a leading professional services company based in Minneapolis, MN, US. CLA operates in the accounting industry and offers a broad range of products and services such as wealth advisory, outsourcing, audit, tax, and consulting services. The company was founded in 1953 with a merger between two firms, Clifton Gunderson and LarsonAllen, in 2012. Working in accordance with their mission to create opportunities for clients, people, and communities, they have established a presence across the US, serving privately held businesses, non-profits, and governmental entities. Recognized for their contributions, CLA has received accolades such as the Innovative Firm of the Year award.

Industry

Accounting services

Company size

5,001 - 10,000 Employees

Headquarters location

Minneapolis, MN, US

Year founded

2012

View All CliftonLarsonAllen Jobs

Apply