ZipRecruiter

Log In

1

Applied Statistics Jobs in Wisconsin (NOW HIRING)

Wisconsin

Data Scientist II or III

Madison, WI · On-site

$85K/yr

At least five years of relevant experience in health-related applied research, statistics, and analytics. * Advanced proficiency with statistical software and programming languages, specifically ...

6AM City

Post Doctorate Research Associate

Wausau, WI · On-site +1

The Associate will support and lead a diverse portfolio of applied research projects aimed at ... quantitative and statistical skills (R, Python, or equivalent) Expertise in GIS and spatial ...

6AM City

Post Doctorate Research Associate

Wausau, WI · On-site +1

The Associate will support and lead a diverse portfolio of applied research projects aimed at ... quantitative and statistical skills (R, Python, or equivalent) Expertise in GIS and spatial ...

Tiger Analytics

WI · On-site

Utilize advanced statistical techniques and data science algorithms to analyze large datasets and ... MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a ...

previous page

Showing results 41-60

All JobsApplied Statistics JobsApplied Statistics Jobs in Wisconsin

Applied Statistics information

See Wisconsin salary details

$40.9K

$84.4K

$118.1K

How much do applied statistics jobs pay per year?

As of Aug 13, 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.

What does an applied statistics do?

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 is an applied statistics?

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.

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 languages like R or Python. It offers diverse opportunities across industries such as healthcare, finance, and technology, with competitive salaries and growth potential. Success typically depends on strong analytical skills, statistical knowledge, and the ability to communicate findings effectively.

What can 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 using tools like R or Python. Graduates can work in industries like healthcare, finance, marketing, or technology, often requiring strong analytical skills and knowledge of statistical methods. Certifications in data analysis or machine learning can enhance job prospects.

What are the key skills and qualifications needed to thrive in applied statistics?

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:

Applied Statistics jobs near you
Infographic showing various Applied Statistics job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% 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.

Digital Personalization Analytics Expert (Remote)

KOHLS

Menomonee Falls, WI • On-site

Other

Re-posted 11 days ago

Kohl's rating

5.8

Company rating: 5.8 out of 10

Based on 1,464 frontline employees who took The Breakroom Quiz

13th of 21 rated department stores

Job description

This position can be remote; however, if you reside near our offices in Menomonee Falls, WI, or New York City, NY, we request that you work onsite from Monday through Thursday, with the option to work remotely on Fridays.

About the Role

In this role you will ensure the creation of best-in-class digital experiences for Kohl’s customers using advanced analytics geared toward diagnostics, customer-level 1:1 modeling and in-market testing.

What You’ll Do

  • Leverage large-scale data and advanced analytics to optimize digital customer engagement and lifetime value

  • Lead end-to-end data science initiatives, from problem framing and exploratory analysis through model development, validation and production deployment

  • Drive consolidation of insights across digital initiatives to continuously enhance data-driven targeting and personalization strategies

  • Oversee test design and activation, ensuring model execution, audience segmentation and timelines are delivered effectively to stakeholders

  • Establish rigorous documentation standards for analytics assets, experiments and insights to enable knowledge sharing and scalability

  • Mentor junior data scientists, providing technical guidance and fostering a culture of continuous learning and excellence

  • Represent the Data Science team in cross-functional forums, independently communicating methodologies, results and strategic implications

  • Champion production-grade machine learning practices, promoting scalable code and robust deployment standards

  • Stay current on emerging data science methodologies and technologies, identifying and driving innovation opportunities that create business impact

  • Establish and maintain strong working relationships and achieve results by working collaboratively with others

  • Additional tasks may be assigned

What Skills You Have

Required

  • Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related quantitative field

  • 5+ years (or 2+ years with a Master’s degree) of progressively complex data science experience

  • Expertise in developing and deploying state-of-the-art algorithms using machine learning, statistical and optimization methods to power various aspects of highly complex business models and deliver value

  • Expert in using modern analytics tools, programming languages and cloud platforms (Python, R, Spark, SQL, GCP, etc.), as well as version control systems such as GitHub

  • Strong problem-solving skills with experience proposing rapid experiments to test the effectiveness of new strategies or initiatives and iterating quickly

  • Experience with data visualization technologies such as Streamlit, R Shiny, Looker, Qlik, Tableau, etc.

Preferred

  • Master's degree and/or Ph.D.

  • Digital / Ecommerce data science experience

  • Retail and Marketing experience

What Kohl's employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply