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Predictive Modeling Jobs in Arizona (NOW HIRING)

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

Business Analytics Tutor

Mesa, AZ · Remote

$18 - $40/hr

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Business Analytics Tutor

Tempe, AZ · Remote

$18 - $40/hr

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

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Predictive Modeling information

See Arizona salary details

$9

$54

$77

How much do predictive modeling jobs pay per hour?

As of Jul 2, 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 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 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:
Data Scientist, Senior

$114K/yr

Full-time

Posted 21 days ago


Arizona State University rating

7.6

Company rating: 7.6 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

248th of 544 rated colleges and universities


Job description

Job Profile:
Business and Data Analyst 3
Job Family:
Business and Data Analytics
Time Type:
Full time
Max Pay - Depends on experience:
$114,000.00 USD Annual
Apply before 11:59 PM Arizona time the day before the posted End Date.
Minimum Qualifications:
Bachelor's degree and five (5) years of experience appropriate to the area of assignment/field; OR, Any equivalent combination of experience and/or training from which comparable knowledge, skills and abilities have been achieved.
Job Profile Summary:
Defines systems requirements, makes recommendations for technology selection, and performs moderately complex data analysis to ensure data management objectives within a work unit are met.
Job Description:
Supports ASU's Actionable Analytics initiatives through the application of advanced data science, machine learning, statistical analysis, and artificial intelligence techniques, including the use of large language models (LLMs) and other foundation model technologies. Serves as a senior-level contributor responsible for designing, developing, validating, deploying, and monitoring analytical and AI-enabled solutions that address operational and strategic organizational needs.
Position Salary Range:
  • $90,000 - $114,000 per year, DOE

Essential Duties:
  • Leverages machine learning, artificial intelligence, large language models (LLMs), and other advanced analytical techniques to develop innovative solutions that address operational and strategic institutional needs.
  • Promotes the responsible, ethical, secure, and compliant use of data science, machine learning, and artificial intelligence technologies in accordance with institutional policies and applicable regulations.
  • Determines and develops advanced research design methodologies, data analysis approaches, statistical modeling procedures, machine learning solutions, and generative AI applications to meet operational and strategic organizational needs.
  • As part of a team, conducts all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing deployment, monitoring, evaluation, and ongoing support.
  • Selects and applies advanced statistical, predictive modeling, machine learning, large language model (LLM), and generative AI techniques to generate actionable insights and address complex organizational challenges using structured and unstructured data sources.
  • Develops, deploys, integrates, and maintains statistical models, machine learning models, and AI-enabled solutions, including applications leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in development and production environments.
  • Implements monitoring and evaluation processes for statistical models, machine learning models, and AI-enabled solutions to assess performance and enable continuous improvement.
  • Collaborates with technical and non-technical stakeholders to translate business needs into analytical solutions and actionable recommendations.
  • Creates and maintains technical documentation, analytical workflows, and model documentation.
  • Supports the adoption of machine learning operationalization (MLOps/AIOps) practices, including version control, model deployment, workflow automation, and reproducibility.
  • Learns, evaluates, and adopts new analytical methodologies, technologies, and tools to meet changing organizational needs.
  • Presents analytical findings and recommendations through written reports, presentations, and data visualizations to technical and non-technical stakeholders.
  • Provides technical guidance and mentorship to junior staff members and project teams as appropriate.

Desired Qualifications:
  • Demonstrated knowledge of and experience applying generative AI and large language model (LLM) technologies, using a wide-ranging suite of structured and unstructured data sources and success outcomes, as well as advanced traditional and modern/machine learning predictive modeling methodologies.
  • Experience conducting all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing, deployment, monitoring, evaluation, and ongoing support.
  • Experience developing, validating, deploying, and maintaining machine learning models and AI-enabled applications, including solutions leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in cloud or production environments.
  • Demonstrated knowledge of machine learning and AI best practices, including cross-validation, hyperparameter tuning, prompt optimization, model monitoring, performance evaluation, explainability, and responsible AI principles.
  • Experience evaluating, selecting, and applying large language models (LLMs), foundation models, and generative AI technologies to support knowledge discovery, workflow automation, decision support, and business process improvement.
  • Proficiency in Python and SQL, including experience leveraging libraries, frameworks, and APIs used for machine learning, data science, and generative AI applications.
  • Demonstrated working knowledge of higher education data systems, including specialized data mining, natural language processing, knowledge discovery, and data visualization techniques.
  • Experience using cloud-based analytics, machine learning, and AI services to develop, deploy, monitor, and support analytical and AI-enabled solutions.
  • Experience using version control systems and collaborative development tools.
  • Experience using data visualization tools and techniques to communicate complex analytical findings and insights.
  • Demonstrated ability to clearly and accurately summarize findings and recommendations to technical and non-technical stakeholders to inform decision making.
  • Demonstrated ability to lead complex analytical projects, prioritize competing demands, and complete projects on time and within scope.
  • Demonstrated ability to work effectively both independently and collaboratively as part of a team.
  • Demonstrated ability to translate stakeholder needs into appropriate, functional, and informative analytical and AI-enabled solutions.
  • Experience mentoring or providing technical guidance to analysts, data scientists, or project teams.

Working Environment:
  • Activities are performed in an environmentally controlled office setting subject to extended periods of staying in a stationary position, manipulating a computer 75 percent; required to traverse moderate distances to perform work 10 percent. Ability to clearly express oneself and effectively exchange information to perform essential functions. Frequent moving, transporting, and positioning up to 25 pounds 15 percent. Regular activities require ability to quickly change priorities, which may include or are subject to resolution of conflicts.

Department Statement:
Actionable Analytics, within the Office of the University Provost, advances studentsuccess by developing and supporting innovative enterprise analytics applications anddata solutions for the Academic Enterprise. The department provides trusted data, datascience solutions, actionable insights, and decision support tools that empower studentsuccess initiatives for ASU campus-immersion and digital-immersion students.
Driving Requirement:
Driving is not required for this position.
Location:
Campus: Tempe
Funding:
No Federal Funding
Instructions to Apply:
Current employees, student workers seeking staff opportunities, and students applying for student worker positions must apply directly through the Workday Jobs Hub.
Please use the link below to log in using single sign-on.
https://www.myworkday.com/asu/d/inst/1$9925/9925$23236.htmld
To be considered, your application must include all of the following attachments:
  • Cover letter
  • Resume or CV

Multiple documents may be uploaded in the attachments section. Alternatively, applicants may combine all required materials into a single PDF for submission. Please ensure uploaded documents are clearly labeled and include your name.
Please ensure your resume includes all employment information in month and year format, for example 6/04 to 8/14, along with job title, job duties, and employer name for each position. Your resume should clearly demonstrate how your experience and background meet the minimum and desired qualifications for this position. Incomplete applications or missing required materials may not be considered.
Important: Do not withdraw your application to make edits. Once an application is withdrawn, it cannot be edited, reactivated, or replaced with a new submission. If you have questions or need assistance, please contact The Office of Human Resources Talent Acquisition before the posting close date.
Graduate Assistant, Intern and part-time positions are counted as half time for experience equivalency, meaning one year equals six months of experience.
Only electronic applications will be accepted for this position. By submitting an application, you confirm that the information provided is accurate and complete.
ASU Statement:
Arizona State University is a new model for American higher education, an unprecedented combination of academic excellence, entrepreneurial energy and broad access. This New American University is a single, unified institution comprising four differentiated campuses positively impacting the economic, social, cultural and environmental health of the communities it serves. Its research is inspired by real world application blurring the boundaries that traditionally separate academic disciplines. ASU serves more than 100,000 students in metropolitan Phoenix, Arizona, the nation's fifth largest city. ASU champions inclusive excellence, and welcomes students from all fifty states and more than one hundred nations across the globe.
ASU is a tobacco-free university. For details visit https://wellness.asu.edu/explore-wellness/body/alcohol-and-drugs/tobacco
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other basis protected by law.
Notice of Availability of the ASU Annual Security and Fire Safety Report:
In compliance with federal law, ASU prepares an annual report on campus security and fire safety programs and resources. ASU's Annual Security and Fire Safety Report is available online at https://www.asu.edu/police/PDFs/ASU-Clery-Report.pdf. You may request a hard copy of the report by contacting the ASU Police Department at 480-965-3456.
Relocation Assistance - For information about schools, housing child resources, neighborhoods, hospitals, community events, and taxes, visit https://cfo.asu.edu/az-resources.
Employment Verification Statement:
ASU conducts pre-employment screening which may include verification of work history, academic credentials, licenses, and certifications.
Background Check Statement:
ASU conducts pre-employment screening for all positions which includes a criminal background check, verification of work history, academic credentials, licenses, and certifications. Employment is contingent upon successful passing of the background check.
Fingerprint Check Statement:
This position is considered safety/security sensitive and will include a fingerprint check. Employment is contingent upon successful passing of the fingerprint check.

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