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Predictive Modeling Analyst Jobs (NOW HIRING)

AAA

Senior Actuarial Predictive Modeler

Coppell, TX · On-site

The role supports complex, end-to-end pricing initiatives--from exploratory analysis and model development through governance, implementation, and monitoring. The Senior Actuarial Predictive Modeler ...

AAA

Senior Actuarial Predictive Modeler

Saint Louis, MO · On-site

The role supports complex, end-to-end pricing initiatives--from exploratory analysis and model development through governance, implementation, and monitoring. The Senior Actuarial Predictive Modeler ...

AAA

Senior Actuarial Predictive Modeler

Coppell, TX · On-site

The role supports complex, end-to-end pricing initiatives--from exploratory analysis and model development through governance, implementation, and monitoring. The Senior Actuarial Predictive Modeler ...

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Predictive Modeling Analyst information

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$33K

$99.4K

$187K

How much do predictive modeling analyst jobs pay per year?

As of Aug 16, 2026, the average yearly pay for predictive modeling analyst in the United States is $99,430.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $126,000.00 per year, depending on experience, location, and employer.

What does a predictive modeling analyst do?

A Predictive Modeling Analyst uses statistical techniques and data analysis tools to forecast future outcomes based on historical data. They build mathematical models to identify patterns and trends, helping organizations make data-driven decisions in areas like marketing, finance, and operations. Their work often involves cleaning data, selecting relevant variables, and evaluating the accuracy of their models to ensure reliable predictions.

What are the key skills and qualifications needed to thrive as a predictive modeling analyst?

To thrive as a Predictive Modeling Analyst, you need strong statistical analysis, data mining, and mathematical modeling skills, typically supported by a degree in statistics, mathematics, computer science, or a related field. Proficiency with analytical tools and languages such as Python, R, SAS, and familiarity with data visualization software and databases is essential. Critical thinking, problem-solving, and effective communication are key soft skills that help convey complex findings to stakeholders. These skills and qualities are crucial for generating accurate predictions and actionable insights that drive strategic business decisions.

How does a predictive modeling analyst typically collaborate with other departments within an organization?

Predictive Modeling Analysts often work closely with departments such as Marketing, Finance, Operations, and IT to understand business needs and deliver actionable insights. They translate complex statistical findings into clear recommendations, ensuring stakeholders from non-technical backgrounds can make informed decisions. Regular meetings, cross-functional project teams, and data-sharing platforms are common collaboration tools, making strong communication and teamwork skills essential. This collaborative approach not only improves model effectiveness but also helps align predictive analytics with overall business strategies.

What states have the most Predictive Modeling Analyst jobs?

States with the most job openings for Predictive Modeling Analyst jobs include:

Predictive Modeling Analyst jobs near you
Infographic showing various Predictive Modeling Analyst job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $99,430 per year, or $47.8 per hour.

Predictive Data Analyst

Vertisystem Inc.

Los Angeles, CA • On-site

Other

Posted 4 days ago

Job description


(Position Description) The Predictive Data Analyst will support stakeholders by defining data needs and ensuring data science and advanced analytics projects meet business objectives across various levels. The Predictive Data Analyst will use statistical programming languages and tools for data manipulation, analysis, and visualization, including end-to-end predictive modeling from exploratory analysis to deployment and results interpretation. The Predictive Data Analyst will manage data through querying, merging, quality control, regular reporting, special project deliverables, and documentation. Additionally, the Predictive Data Analyst will collaborate with IT and data engineering staff to develop data pipelines, designs and maintains reports and dashboards, and will work directly with program staff to ensure analyses lead to actionable insights for decision-making and program improvement. The Predictive Data Analyst will serve as the Subject Matter Expert (SME) on cross-agency justice-involved datasets and managed care plan reporting, owning the associated business logic, query design, and report definitions. Functioning as a technical lead within a collaborative team structure, the Predictive Data Analyst will consult on the technical feasibility of project intakes, takes a lead role on Tableau dashboard development, or similar, and API reporting, and drives rigorous quality assurance. The Predictive Data Analyst will handle technical documentation and actively engages in team Agile/Scrum workflows by participating in daily stand-ups, backlog grooming, and sprint planning to commit to and deliver technical tasks. (Skills Required) The Predictive Data Analyst will possess knowledge and experience in predictive analytics and tool development; ability to work directly with a client-centric relational database; have strong technical knowledge to conduct analysis and build reports from an SQL database; comfortable with various analytical tools; ability to take the lead on projects where the best path forward is unclear; excellent interpersonal, oral and written communication skills; and exceptional customer service.

Miscellaneo Niche/ Other

Four (4) years of experience with responsibility for planning, designing, conducting, and evaluating research projects involving the application of techniques of machine learning, predictive analytics, data management, and hypothesis-driven data analysis to complex experimental designs, leading to actionable findings and recommendations.

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