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Data Scientist Machine Learning Jobs in Wisconsin

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Showing results 41-60

Data Scientist Machine Learning information

See Wisconsin salary details

$37.9K

$123.9K

$198.3K

How much do data scientist machine learning jobs pay per year?

As of Sep 11, 2026, the average yearly pay for data scientist machine learning 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.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What is the salary of data scientist in machine learning?

The salary of a data scientist specializing in machine learning typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in programming, statistical analysis, and tools like Python or TensorFlow may earn higher compensation.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Wisconsin?

The most popular types of Data Scientist Machine Learning jobs in Wisconsin are:

What are popular job titles related to Data Scientist Machine Learning jobs in Wisconsin?

For Data Scientist Machine Learning jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Data Scientist Machine Learning jobs in Wisconsin look for?

The top searched job categories for Data Scientist Machine Learning jobs in Wisconsin are:

Infographic showing various Data Scientist Machine Learning job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $123,886 per year, or $59.6 per hour.

Machine Learning Engineer II

Brookfield, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 26 days ago


Job description

Job Description:
Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.
At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions on our engineering teams. Our Engineering Team is responsible for giving life to the batteries, motors, and electronics that power solutions changing the lives of our users. Every developmental phase of these critical components happens in-house under the watch of this team. We continue to invest in engineering resources to design and develop leadership in electronic capabilities; something unique within the industry. And we're pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.
Your role on our team
As a Machine Learning Engineer II, you will create, develop, and validate machine learning models while working with highly cross-functional teams to make power tool solutions that change the lives of our users. You will innovate and explore new machine learning solutions to deploy into Milwaukee products around the world while demonstrating excellent problem-solving skills, critical thinking, and the ability to thrive under pressure in a dynamic environment. Success in this role also requires strong technical communication skills and fundamental project management abilities, along with a proactive sense of ownership for projects and tasks and an understanding of how they connect to broader initiatives.
What TOOLS you'll bring with you:
  • Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
  • Completed course work or specialization in Machine Learning and/or Data Science
  • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field
  • Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
  • Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
  • Proficient developing and debugging code in Python
  • Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
  • Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
  • Sold mathematical foundation in statistics, linear algebra, calculus and optimization
  • Experience working with modern software development tools and version control tools
  • Excellent problem-solving skills, critical thinking, and ability to work well under pressure in a dynamic environment.
  • Excellent technical communication skills and fundamental project management abilities
  • Demonstrated strong sense of ownership of a project or tasks and understanding of relationships to other tasks/projects
  • Ability to travel up to 10% of the time (domestic and international).

Other TOOLS we prefer you to have:
  • Master's degree or PhD in Machine Learning or related field is preferred
  • At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field (an advanced degree may count toward some experience)
  • Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
  • Proven track record of developing, deploying and implementing AI or ML solutions connected to business objectives
  • Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
  • Working knowledge of various sensor technologies (e.g. IMU, thermistors, magnetic and optical) and interfacing to microcontrollers
  • Working knowledge of embedded systems architecture (HW & SW), microcontroller design and operation
  • Experience with different types of data collection methods, understanding their principles and demonstrating their value in relevant environments
  • Experience developing and deploying machine learning algorithms to edge environments
  • Demonstrated ability to develop robust MLOps pipelines and ensure efficient deployment, monitoring and scaling of ML models

We provide these great perks and benefits:
  • Robust health, dental and vision insurance plans.
  • Generous 401 (K) savings plan.
  • Education assistance.
  • On-site wellness, fitness center, food, and coffee service.
  • And many more, check out our benefits site HERE.

Milwaukee Tool is an equal opportunity employer.