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Predictive Modeling Jobs in Wisconsin (NOW HIRING)

ATI

Data Scientist

Cudahy, WI · On-site

Experience in deep learning, predictive modeling, data mining, and time series analysis. * Knowledge of image segmentation, generative models, convolutional neural networks. * Experience in applied ...

CLA (CliftonLarsonAllen)

Senior AI Engineer

Madison, WI · On-site

$105K - $144K/yr

Responsibilities : • Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications • Design end-to-end architectures including data ...

CLA (CliftonLarsonAllen)

Senior AI Engineer

Racine, WI · On-site

$98K - $134K/yr

Responsibilities : • Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications • Design end-to-end architectures including data ...

Generac

Senior Platform & Analytics Analyst

Waukesha, WI

$86K - $108K/yr

The Senior Analyst, Analytics and Platform is responsible for analyzing manufacturing data to create dashboards, reports, and predictive models that identify trends and support optimizations in ...

Cliftonlarsonallen

Senior AI Engineer

Racine, WI

$98K - $134K/yr

Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications * Design end-to-end architectures including data pipelines, APIs, model ...

Cliftonlarsonallen

Senior AI Engineer

Madison, WI

$105K - $144K/yr

Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications * Design end-to-end architectures including data pipelines, APIs, model ...

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Predictive Modeling information

See Wisconsin salary details

$10

$59

$83

How much do predictive modeling jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for predictive modeling in Wisconsin is $59.26, according to ZipRecruiter salary data. Most workers in this role earn between $53.12 and $68.89 per hour, depending on experience, location, and employer.

What is the highest paying modeling job?

In predictive modeling, senior data scientists and machine learning engineers typically earn the highest salaries, often exceeding six figures annually. These roles require advanced skills in statistical analysis, programming, and experience with tools like Python or R, and they are often found in industries such as finance, technology, and healthcare.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is a Predictive Modeling job?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or SAS and often require strong analytical skills and knowledge of data science techniques. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R, often through online courses or certifications. Success depends on your ability to learn and apply relevant skills, regardless of age.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What jobs will no longer exist in 2030?

Predictive modeling roles may decline as automation and AI tools increasingly handle data analysis and forecasting tasks. Jobs that involve routine, repetitive tasks are also at risk of automation, potentially reducing demand for certain administrative or manual roles. However, new jobs may emerge in AI oversight, data ethics, and advanced analytics.
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Predictive Modeling jobs near you
Senior Data Scientist

Senior Data Scientist

The Weather Channel

Madison, WI

Full-time

Posted 2 days ago

Job description

Company Description

The Weather Company provides the best weather insight in the world, and is leading the charge in the growing area of weather decision support for business. We are offering you a unique opportunity to apply and/or develop your mathematical modeling skills on our unique set of weather data. Working with weather data is really unique and amazing; weather is in perpetual evolution, generates petabytes of new data every month, and deeply impacts people and businesses on various timescales. We serve a wide variety of businesses including renewable energies, energy traders, utility companies, insurance, retailers, and consumer product groups. As a consequence you will apply and/or learn a wide variety of statistical techniques including time series analysis, high dimensional clustering, machine learning, data mining and Bayesian modeling.

Job Description

Are you interested in applying machine learning or data mining on problems that truly improve people's life? We're looking for a mathematician/data scientist eager to tackle unique challenges in the realm of predicting weather's impact on business. You will work on a skilled team of passionate data scientists and meteorologists. Examples of projects you may encounter would be anything from predicting the electricity output of a solar park in Arizona, to predicting how much ice cream is going to be sold next week in Chicago.

  • Partner collaboratively with the business and project teams to accomplish tasks/milestones/goals.

  • Research, recommend, and implement statistical post process correction techniques using proprietary forecasts.

  • Demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, etc.

  • Improve operations by conducting systems analysis; recommending changes in policy and procedures.

  • Provide estimates of work effort and impact of projects and tasks, and provide team leadership, as required.

  • Continuously build your knowledge by studying new scientific methodologies and techniques.

  • Play an active role in the product requirements process, giving feedback to product management when challenges arise.

Qualifications

  • MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series Analysis, Machine learning and Forecasting, or other related discipline.

  • 3-5 years of relevant professional experience, with demonstrated achievements.

  • Can demonstrate mastery of general scientific computing softwares such as R, MATLAB, Octave, etc.

  • Experience using/implementing non-parametric regression such as  Neural Net, SVM, Random Forest, Projection Pursuit, MARS, Radial Basis Functions, AdaBoost, GLM

  • Experience in Predictive Modeling including Non-Parametric Regression, Bayesian Inference, Hidden Markov Models, Generalized ARMA, or Kalman Filtering is a plus.

  • Experience in non-linear optimisation including Simulated Annealing, Genetic Algorithm, Agent Based Modeling, Particle Swarm, Bee Colony is a plus but not necessary.

  • Knowledge of ensemble learning techniques and probabilistic forecasts is a plus.

  • Programming capabilities including C++, Java, Python is a plus but not necessary.

Additional Information


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