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Data Science Jobs in Milwaukee, WI (NOW HIRING)

Generac

Data Science Analyst

Waukesha, WI

In the role of Data Science Analyst working onsite in Waukesha, Wisconsin you will be part of the Data Analytics and Business Intelligence team. The Data Science Analyst is responsible for the ...

KOHLS

Data Scientist (Remote)

Menomonee Falls, WI · On-site

About the Role In this role you will work with a data science team and cross-functional partners to solve business challenges and promote data-driven decision making with advanced data analysis and ...

ATI

Data Scientist

Cudahy, WI · On-site

Serve as a subject matter expert in the capabilities of Data Science. * Collaborate with business owners to solve business problems using a broad spectrum of data science tools, packages and ...

Next Gen Alloys

Data Scientist

Cudahy, WI · On-site

Serve as a subject matter expert in the capabilities of Data Science. * Collaborate with business owners to solve business problems using a broad spectrum of data science tools, packages and ...

ATI

Data Scientist

Cudahy, WI

Serve as a subject matter expert in the capabilities of Data Science. * Collaborate with business owners to solve business problems using a broad spectrum of data science tools, packages and ...

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All JobsData Science JobsData Science Jobs in Milwaukee, WI

Data Science information

See Milwaukee, WI salary details

$36.9K

$120.9K

$193.6K

How much do data science jobs pay per year?

As of Jul 29, 2026, the average yearly pay for data science in Milwaukee, WI is $120,927.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $134,000.00 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 Milwaukee, WI? The most popular types of Data Science jobs in Milwaukee, WI are:
What are popular job titles related to Data Science jobs in Milwaukee, WI? For Data Science jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Milwaukee, WI look for? The top searched job categories for Data Science jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Data Science jobs? Cities near Milwaukee, WI with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Milwaukee, WI as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $120,927 per year, or $58.1 per hour.
Data Science Analyst

Data Science Analyst

Generac

Waukesha, WI

Full-time

Posted 21 days ago

Generac Power Systems rating

7.0

Company rating: 7.0 out of 10

Based on 66 frontline employees who took The Breakroom Quiz

351st of 486 rated machine equipment manufacturers

Job description

We believe power is a promise - a shared commitment to be there for others when it matters most.

For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future.


Ready to Power a Smarter World with us?


In the role of Data Science Analyst working onsite in Waukesha, Wisconsin you will be part of the Data Analytics and Business Intelligence team.

The Data Science Analyst is responsible for the analysis of structured and unstructured data using various techniques, e.g. statistical analysis, explanatory and predictive modeling, data mining. The candidate will determine best practices and develop actionable insights and recommendations for the current operations or issues and works closely with the business functional team to identify analytical requirements. The candidate will work on Enterprise data platform and other analytical projects as needed, assist in implementing or developing systems to capture operational information, and may assist less experienced analysts. The candidate must have familiarity with the manipulation of unstructured data in a data analytics environment, and the use of open-source tools, cloud computing, machine learning and data visualization and appropriate, relevant programming languages.

*This is not a remote role, the ideal candidate will need to be located in Wisconsin, due to this position being onsite and reporting into our Waukesha Headquarters*

Minimum Qualifications:

  • Bachelor Degree

  • 1 year work experience in Math, Statistics, or Computer Science

Preferred Qualifications:

  • Relational database experience & Experience query databases (ex: SQL, MySql).

  • Experience with one or more statistical analysis tools (ex: MatLab, MiniTab, SPSS, or R).

  • Experience with statistical analysis languages (ex: R, Python, SQL).

  • Experience on using the cloud platform (ex Azure, AWS..)

  • Experience with building agents using Microsoft CoPilot, and other solution paths

Essential Duties:

  • Develop and analyze various data to support Enterprise Transformation initiatives and AI use cases

  • Supports data preparation for analytic efforts by cleaning data to ensure quality and accuracy based on provided guidelines; and consolidating data.

  • Translating business requirements; informing data/information needs and data collection methods

  • Create custom data models & create pipelines and algorithms as needed & produce Data insights

  • Assists with data and information gathering for targeted variables in an established systematic fashion by cleaning and organizing data; querying, merging, and extracting data across sources; completing routine data refresh and update; and providing user support and documentation.

  • Supporting end-users; and documenting processes and deliverables

  • Ongoing reports highlighting the initiative progress and successes.

Knowledge and Skills:

  • Ability to write complex SQL queries, data visualization

  • Proficiency in database applications and MS Office with excellent Excel skills.

  • Requires excellent analytical, organization, project management, communication, presentation and people skills with a variety of audiences, up to and including, the executive level.

  • Ability to simplify complex findings to develop unique, practical solutions.

  • Able to understand various data structures and common methods in data transformation.

  • Excellent pattern recognition and predictive modeling skills.

  • Cross/multi-functional understanding of industry, company, and products to enable identification of assumptions and events, and qualification of related risks and opportunities.

  • Self-motivated and able to work with minimal direction

#LI-BB1

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 occasionallylift upto 25 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision, and the 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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