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Predictive Modeling Jobs in Arizona (NOW HIRING)

Geico

Senior Workforce Analytics Analyst

Tucson, AZ · Hybrid

$80K - $124K/yr

Collaborate with teams developing predictive models to enhance forecasting accuracy and optimize staffing plans. Reporting & Visualization: * Create and maintain detailed reports and dashboards using ...

AssetMark

Vice President, Analytics

Phoenix, AZ

Deep expertise in business intelligence, advanced analytics (predictive modeling, segmentation, forecasting), machine learning, and cloud data platforms (Snowflake, AWS, Azure). * Proficient with ...

Vangard, Inc.

Data Analyst, Specialist

Scottsdale, AZ · On-site

Python & Advanced analytics (e.g. predictive modeling, forecasting, clustering) experience preferred. Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About ...

Mercer

Client Partner

Phoenix, AZ · On-site +1

Strong strategic and analytical mindset, with experience leveraging HR data analytics, predictive modeling, and digital process optimization to drive decision-making. * Deep expertise in project and ...

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How much do predictive modeling jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for predictive modeling in Arizona is $54.71, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $63.61 per hour, depending on experience, location, and employer.

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 specialized software and often require knowledge of data analysis, statistics, and programming. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

What jobs make $1,000,000 a year?

In predictive modeling, high-earning roles such as senior data scientists, machine learning engineers, and analytics directors can reach or exceed $1 million annually, especially in top tech companies or financial firms. These positions typically require advanced skills in statistical analysis, programming, and experience with big data tools, along with leadership responsibilities and often performance-based bonuses or equity.

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. Continuous learning and relevant experience are more important than age when pursuing a data science career.

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 job makes $10,000 a month without a degree?

Predictive modeling roles, such as data scientists or machine learning engineers, can earn $10,000 or more per month with significant experience and expertise in statistical analysis, programming, and data tools. These jobs often require strong skills in Python, R, or SQL and may involve working in tech, finance, or consulting environments, but typically do not require a formal degree if skills are demonstrated through portfolios or certifications.
What are the most commonly searched types of Predictive Modeling jobs in Arizona? The most popular types of Predictive Modeling jobs in Arizona are:
What are popular job titles related to Predictive Modeling jobs in Arizona? For Predictive Modeling jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Predictive Modeling jobs in Arizona look for? The top searched job categories for Predictive Modeling jobs in Arizona are:
Predictive Modeling jobs near you
Statistical Scientist (M.S. or Ph.D.)

Statistical Scientist (M.S. or Ph.D.)

Exponent

Phoenix, AZ • On-site

Full-time

Posted 20 days ago

Job description

Job Summary:
Exponent is a premium engineering and scientific consulting firm that seeks to empower clients with innovative solutions. The Statistical Scientist will be responsible for conducting exploratory data analysis, applying risk analysis methodologies, and developing reports and visualizations to address clients’ scientific and engineering challenges.
Responsibilities:
• Participating in diverse projects involving exploratory data analysis, statistical inference, and predictive modeling
• Applying risk analysis methodologies to problems in engineering, health, finance, ecology, and the environment
• Providing support to internal and external clients when planning data collection, including framing the problem, experimental design, sample size calculations, and identifying appropriate populations and sampling strategies
• Developing reports and visualizations to address clients’ scientific and engineering problems and to support litigation
Qualifications:
Required:
• Ph.D. (or M.S. degree with two years' work experience post-graduation) in Statistics, Biostatistics, or a related field
• Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences
• Experience or capabilities in such subject areas as statistical data mining, analysis of reliability and life data, experimental design, Bayesian statistics, machine learning, or quality control/improvement
• Minimum of two years' experience with one or more statistical software packages (SAS and R are preferred)
• Ability to work independently and in multidisciplinary teams
• Presently legally authorized to work in the United States; no immigration sponsorship or processing required
Preferred:
• Programming skills (e.g., C++, SQL, Visual Basic, Python) and software or dashboard development experience are strongly preferred
Company:
With over 90 scientific and engineering disciplines, Exponent’s staff of approximately 900, located in 20 offices throughout the USA Founded in 1967, the company is headquartered in Menlo Park, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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