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Predictive Modeling Jobs in Wisconsin (NOW HIRING)

Genesys

Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments. * Develop interpretable, production-grade models ...

Genesys

Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments. * Develop interpretable, production-grade models ...

Generac

Data Science Analyst

Waukesha, WI

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 ...

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Predictive Modeling information

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$10

$59

$83

How much do predictive modeling jobs pay per hour?

As of Jul 25, 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.
What are the most commonly searched types of Predictive Modeling jobs in Wisconsin? The most popular types of Predictive Modeling jobs in Wisconsin are:
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What job categories do people searching Predictive Modeling jobs in Wisconsin look for? The top searched job categories for Predictive Modeling jobs in Wisconsin are:
Predictive Modeling jobs near you
Infographic showing various Predictive Modeling job openings in Wisconsin as of July 2026, with employment types broken down into 67% Full Time, 15% Part Time, and 18% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $123,265 per year, or $59.3 per hour.
Senior Predictive Modeling Lead - Actuarial

Senior Predictive Modeling Lead - Actuarial

6AM City

Madison, WI

Full-time

Posted 10 days ago

Job description

Society Insurance seeks a Predictive Modeling Manager within the Actuarial Team in Wisconsin. You will lead modeling projects, verify data, design data structures, and maintain documentation of methods and results, while collaborating with stakeholders to ensure compliance. You will mentor team members, set testing standards, and influence vendor selections, leveraging your strong SQL/Excel skills and actuarial knowledge to improve processes and outcomes. #J-18808-Ljbffr

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