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Data Science Jobs in Wisconsin (NOW HIRING)

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 ...

KOHLS

Data Scientist I (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 ...

KOHLS

Data Scientist II (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 ...

Newance

Senior Data Scientist

Green Bay, WI · On-site

As a member of our Data Science team, you will play a crucial role in leveraging, building and developing analytical tools to solve complex business problems. You will also be expected to act as ...

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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 23, 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 July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $123,886 per year, or $59.6 per hour.

Data Scientist

Next Gen Alloys

Cudahy, WI • On-site

Full-time

Posted 21 days ago

Job description

Proven to Perform.
From the edges of space to the bottoms of ocean, our materials are proven to perform -- and so is our team. We're hiring high performers as proven as our products. Join us.

ATI is seeking to hire a Data Scientist to support business unit-wide data analytics initiatives. This position will be based in Cudahy, WI.

As a Data Scientist your work may be focused in a variety of areas, including Machine learning predictions of material properties, thermal management of forgings, automated characterization methods, and design and improvement of manufacturing processes.

A successful Data Scientist will work cross-functionally across multiple levels, operate effectively in early-stage development of processes and procedures, and will possess a strong Continuous Improvement mindset.

Additional Responsibilities

  • Map data from multiple sources into new structures.
  • Work with business subject matter experts to determine best solutions
  • 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 visualization techniques.
  • Build models and optimization tools to support large scale projects that utilize online, offline data, structured, and unstructured data.

Basic Qualifications

  • B.S. degree in computer science, engineering with a strong statistical and programming background.
  • Experience in deep learning, predictive modeling, data mining, and time series analysis.
  • Knowledge of image segmentation, generative models, convolutional neural networks.
  • Experience in applied machine learning.

Preferred Qualifications (in addition to Basic Qualifications)

  • Experience in PyTorch, Keras/Tensorflow.
  • Experience in explainable AI.
  • Experience in SQL data query, data cleaning
    • Experience in SAP Data Intelligence and/or Azure cloud computing a plus but not required.
  • If you have worked on PINN or used ML for solving materials science problem a big plus.

Wethrive when the expectations are great, and the barriers are high. We're solving the world's most difficult challenges through materials science.Our advanced, integrated process technologies and proven performers give us a tremendous competitive advantage. When customers systems need to fly higher, dig deeper, stand stronger, and last longer -- anywhere on, above or below the earth -- ATI is proven to perform.

*It is ATI's policy to not provide immigration sponsorship for any of the company's positions.
ATI and its subsidiary companies will provide equal employment opportunities to all applicants without regard to applicant's race, color, religion, sex, gender, genetic information, national origin, age, veteran status, disability status, or any other status protected be federal or state law. The company will provide reasonable accommodations to allow an applicant to participate in the hiring process if so requested.

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