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Physics Data Analyst Jobs in Wisconsin (NOW HIRING)

Ametek

R&D Scientist

Madison, WI · On-site

MS or PhD in Materials Science, Engineering, Physics, or a related field (required) * 6-8 years of ... Experience with data analysis and modeling tools (Mathematica or MATLAB preferred) * Demonstrated ...

Socket.dev

WI · On-site

$110 - $190/hr

  • Retirement

Perform Gaussian beam optics analysis and diffraction simulations to characterize beam propagation ... Interact with other engineering and physics disciplines including thermal, mechanical, and ...

trane technologies

Controls Algorithm Engineer

La Crosse, WI · On-site

$82K - $106K/yr

  • Medical

  • Retirement

  • PTO

Lead dynamic controls testing:test planning, lab support, data analysis * Develop and execute ... Bachelor's degree (Mechanical Engineering, Electrical Engineering, Applied Mathematics, Physics or ...

Trane Technologies plc

Controls Algorithm Engineer

La Crosse, WI

$82K - $106K/yr

  • Medical

  • Retirement

  • PTO

Lead dynamic controls testing:test planning, lab support, data analysis * Develop and execute ... Bachelor's degree (Mechanical Engineering, Electrical Engineering, Applied Mathematics, Physics or ...

Trane Technologies plc

Controls Algorithm Engineer

La Crosse, WI · On-site

$82K - $106K/yr

  • Medical

  • Retirement

  • PTO

Develop and execute hardware in loop testing (real time data analysis) * Advance model driven ... Bachelor's degree (Mechanical Engineering, Electrical Engineering, Applied Mathematics, Physics or ...

Jobtailor

WI · On-site

$110 - $140/hr

... applied physics, electrical engineering, physics, materials science, chemistry, chemical ... Expertise in analyzing data leading to informed decision‑making. * Excellent written ...

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Showing results 41-60

All JobsPhysics Data Analyst JobsPhysics Data Analyst Jobs in Wisconsin

Physics Data Analyst information

See Wisconsin salary details

$34.3K

$83.4K

$137.3K

How much do physics data analyst jobs pay per year?

As of Aug 18, 2026, the average yearly pay for physics data analyst in Wisconsin is $83,413.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,100.00 and $97,900.00 per year, depending on experience, location, and employer.

What does a physics data analyst do?

A Physics Data Analyst collects, processes, and interprets large sets of data generated from physics experiments or simulations. They use statistical methods, programming, and specialized software to extract meaningful insights and support scientific research. Their work often involves cleaning data, identifying trends, creating visualizations, and collaborating with physicists to draw conclusions that can advance understanding in areas such as particle physics, astrophysics, or materials science.

What are some common challenges physics data analysts face when interpreting experimental data?

Physics Data Analysts often work with large, complex datasets that may contain noise or inconsistencies due to experimental limitations. One common challenge is accurately distinguishing between meaningful patterns and random fluctuations, which requires strong statistical knowledge and experience with data-cleaning techniques. Additionally, analysts must frequently collaborate with physicists and engineers to understand the context of the data and ensure proper interpretation, making strong communication skills important. Overcoming these challenges involves continually updating technical skills and staying current with best practices in both physics and data analysis.

What are the key skills and qualifications needed to thrive as a physics data analyst, and why are they important?

To thrive as a Physics Data Analyst, you need a solid background in physics, mathematics, and statistical analysis, often supported by a degree in physics or a related field. Proficiency with programming languages like Python or MATLAB, data visualization tools, and familiarity with statistical software and databases are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret complex datasets and share insights with diverse teams. These skills ensure accurate analysis, meaningful data-driven conclusions, and successful collaboration in research or industry environments.

What is the difference between Physics Data Analyst vs Data Scientist?

AspectPhysics Data AnalystData Scientist
Required CredentialsBachelor's or Master's in Physics, Data Analysis, or related fieldsBachelor's or Master's in Computer Science, Statistics, or related fields
Work EnvironmentResearch labs, scientific organizations, industry R&DTech companies, finance, healthcare, consulting
Employer & Industry UsageResearch institutions, aerospace, energyTech firms, finance, marketing
Common Search & ComparisonPhysics Data Analyst vs Data Scientist

The main difference between a Physics Data Analyst and a Data Scientist lies in their focus and industry. Physics Data Analysts typically work in research or scientific environments, applying physics principles to analyze data. Data Scientists have a broader scope, often working across industries like tech, finance, and healthcare, utilizing advanced statistical and machine learning techniques. Both roles require strong analytical skills, but their applications and work settings differ.

What are popular job titles related to Physics Data Analyst jobs in Wisconsin?

For Physics Data Analyst jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Physics Data Analyst jobs in Wisconsin look for?

The top searched job categories for Physics Data Analyst jobs in Wisconsin are:

What cities in Wisconsin are hiring for Physics Data Analyst jobs?

Cities in Wisconsin with the most Physics Data Analyst job openings:

Physics Data Analyst jobs near you
Infographic showing various Physics Data Analyst job openings in Wisconsin as of August 2026, with employment types broken down into 54% Full Time, and 46% Part Time. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $83,413 per year, or $40.1 per hour.

Applied Machine Learning Engineer I - Advanced Engineering & Technology

Milwaukee Tool

Brookfield, WI • On-site

Other

Medical, Dental, Vision, Retirement

Re-posted 6 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.
INNOVATE WITHOUT BOUNDARIES! 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.
Your Role on the Team:
As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will support the research, prototyping, and delivery of ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and support hand-off integrations, delivering technology innovation to product and production engineering teams. This role is an individual contributor position focused on applied execution and technology demonstration, working under shared technical direction.
Why This Role is Different:
  • Full-Stack ML in a Physical Domain: Work across the ML stack, from machine and sensor-level data through model deployment on edge hardware or cloud infrastructure.
  • R&D Engineering First: Apply ML across Technology Readiness Levels (TRL 1-7), bringing technology innovation to life beyond model tuning. Domain knowledge in materials, mechanics, signals, or physics is central to this role.
  • Flexible Tools: Select and use frameworks and libraries best suited to the problem, without being constrained to a single ecosystem.
  • Real Impact: Deliver ML-driven capabilities that shorten product development cycles and unlock new engineering possibilities at Milwaukee Tool.

What You'll Do:
  • Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
  • Frame engineering problems as ML problems by assessing ML value versus physics-based or analytical approaches and defining practical success criteria.
  • Design, train, and evaluate ML models to help solve well-scoped applied science and engineering problems, working under the guidance of senior engineers.
  • Build ML workflows spanning data acquisition, feature engineering, model development, and validation using standard scientific and ML libraries (NumPy, Pandas, scikit-learn, PyTorch, TensorFlow).
  • Support algorithm selection and the construction of standard feature sets for engineering problems.
  • Support the deployment of ML models on edge hardware and cloud infrastructure, building and deploying with guidance.
  • Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
  • Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
  • Conduct experiments and data analysis following established patterns and methods; identify and debug basic model errors.
  • Organize, clean, and prepare data for downstream tasks, and create visualizations that support hypotheses, insights, and conclusions.
  • Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs, and support the design of data collection and test plans.
  • Research and learn about emerging AI and ML technologies through literature, universities, conferences, and vendor engagement.

What You'll Bring:
  • BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
  • Experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
  • Demonstrated experience designing, training, and evaluating ML models on real-world or academic problems.
  • Working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit-learn), with familiarity with SQL.
  • Exposure to at least one deep learning framework (PyTorch or TensorFlow), including training models, and awareness of cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
  • Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
  • Ability to help formulate well-scoped engineering or scientific tasks into ML problems with clear objectives and evaluation criteria, and awareness of when different model classes should be used.
  • Curiosity-driven approach to learning new technologies and methods, with emphasis on applying machine learning to real-world scientific and engineering challenges.
  • Ability to work across a diverse range of data types.
  • Hands-on approach to collaboration and evaluation of technologies.
  • Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
  • Ability to travel 10% of the time (domestic and international).

Preferred
  • Master's Degree in relevant field.
  • Familiarity with common sensors and interpreting their physical data, and exposure to engineering test lab workflows.
  • Experience with computer vision for engineering applications.
  • Awareness of edge deployment concepts: model optimization and containerized deployment to industrial hardware.
  • Coursework or exposure to design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
  • Familiarity with version control, experiment tracking, and reproducible research practices

Working Environment
  • In-Person, Office Environment, R&D Engineering Lab

Our 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.

Apply