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Data Science Jobs in Wisconsin (NOW HIRING)

Elephas

Senior Data Scientist

Madison, WI · On-site

Lead complex, high-visibility data science projects from problem definition through delivery, implementation, ongoing refinement. * Develop and apply advanced statistical, machine learning, and ...

Elephas

Senior Data Scientist

Madison, WI · On-site

Lead complex, high-visibility data science projects from problem definition through delivery, implementation, ongoing refinement. * Develop and apply advanced statistical, machine learning, and ...

Amcor

R&D Senior Manager - Data Science

Neenah, WI · On-site

As a key enabler of digital transformation, this leader oversees a multidisciplinary team spanning data science, business intelligence, and systems management-translating complex materials and R&D ...

Amcor plc

R&D Senior Manager - Data Science

Neenah, WI · On-site

As a key enabler of digital transformation, this leader oversees a multidisciplinary team spanning data science, business intelligence, and systems management-translating complex materials and R&D ...

Fiserv, Inc.

Sr Data Scientist

Milwaukee, WI · On-site

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.

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Data Science information

See Wisconsin salary details

$37.9K

$123.9K

$198.3K

How much do data science jobs pay per year?

As of Jul 2, 2026, the average yearly pay for data science in Wisconsin is $123,886.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,400.00 and $137,300.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Wisconsin? The most popular types of Data Science jobs in Wisconsin are:
What are popular job titles related to Data Science jobs in Wisconsin? For Data Science jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Wisconsin look for? The top searched job categories for Data Science jobs in Wisconsin are:
What cities in Wisconsin are hiring for Data Science jobs? Cities in Wisconsin with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Wisconsin as of June 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $123,886 per year, or $59.6 per hour.
Data Scientist II

Data Scientist II

Generac Power Systems, Inc.

Waukesha, WI • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

We are Generac, a leading energy technology company committed to powering a smarter world.
Over the 60 plus years of Generac's history, we've been dedicated to energy innovation. From creating the home standby generator market category, to our current evolution into an energy technology solutions company, we continue to push new boundaries.
As a senior member of the team, you will have significant responsibility and influence in shaping its future direction. We are looking for someone that leads data science projects from start to finish, defining the problem, identifying opportunities building proofs of concept and implements them as a data product.
You should have deep expertise data science, machine learning and statistical analysis, and the ability to scope out project requirements, time estimates, and resources needed. You should have excellent business and interpersonal skills to be able to work with business owners to understand data requirements, and to build highly scalable systems.
Successful candidates will have strong engineering skills and communication, as well as a belief that data driven processes lead to great products. You will need to have a passion for quality and an ability to understand complex systems.
Essential Duties:
  • We are looking for someone that leads data science projects from start to finish, defining the problem, identifying opportunities building proofs of concept and implements them as a data product.
  • Interact with different teams (Product, Data Platform, Frontend, etc.) to reach common ground and strive for win-win scenarios.
  • Keep updated with the state-of-the-art algorithms and techniques on the field and evaluate them in our business context.
  • Tell engaging data stories for both technical and non-technical audiences.
  • Transform business problems and opportunities into data product solutions.
  • Act as a mentor to junior data scientist.
  • Review pull requests from fellow team members.
  • Evaluate project ideas and provide technology input, prescribing appropriate application solutions, which balance business requirements with Generac's technology standards to arrive at the optimal solution.
  • Write user and technical specifications in line with business needs.

Basic Qualifications:
  • Bachelor's Degree in Computer Science, Math, Physics, Engineering, Statistics or related field,
  • 2+ years of experience post-grad in a Data Science / Machine Learning position.
  • Professional experience with Python.
  • Experience with SQL.
  • Experience with version control (GitHub or similar) in a team environment.
  • Demonstrated experience applying machine learning and data mining techniques.

Preferred Qualifications:
  • Master's and/or PhD are a strong plus
  • Experience in agentic AI across organization
  • Experience in cloud environments (AWS / Azure) are a strong plus

Knowledge, Skills, and Abilities:
  • Strong communication skills and commitment to teamwork
  • Sharp analytical abilities and proven design skills
  • Strong sense of ownership, urgency, and drive
  • Proven leadership abilities in an engineering environment in driving operational excellence and best practices.

Physical Demands: While performing the duties of this job, the employee is regularly required to talk and hear; and use hands to manipulate objects or controls. The employee is regularly required to stand and walk. On occasion the incumbent may be required to stoop, bend or reach above the shoulders. The employee must occasionally lift up to 25 - 50 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision and ability to adjust focus. Occasional travel.
"We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law."

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