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Predictive Analyst Jobs (NOW HIRING)

McKesson

Data Scientist - Predictive Analytics

OR · On-site +1

$108K - $181K/yr

Analyze large, complex datasets to improve forecasting accuracy and operational planning * Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting

MCKESSON

Data Scientist - Predictive Analytics

Columbus, OH · On-site +1

$108K - $181K/yr

Analyze large, complex datasets to improve forecasting accuracy and operational planning * Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting

McKesson

Data Scientist - Predictive Analytics

Columbus, OH · On-site +1

$108K - $181K/yr

Analyze large, complex datasets to improve forecasting accuracy and operational planning * Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting

McKesson

Data Scientist - Predictive Analytics

OR · On-site +1

$108K - $181K/yr

Analyze large, complex datasets to improve forecasting accuracy and operational planning * Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting

McKesson

Data Scientist - Predictive Analytics

Columbus, OH · On-site +1

$108K - $181K/yr

Analyze large, complex datasets to improve forecasting accuracy and operational planning * Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting

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Predictive Analyst information

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How much do predictive analyst jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for predictive analyst in the United States is $45.97, according to ZipRecruiter salary data. Most workers in this role earn between $30.29 and $58.65 per hour, depending on experience, location, and employer.

What does a predictive analyst do?

A predictive analyst uses statistical models and data analysis techniques to forecast future trends and behaviors. They work with large datasets, employ tools like SQL and Python, and interpret results to support decision-making in organizations. Strong analytical skills and knowledge of machine learning are essential for this role.

What are the key skills and qualifications needed to thrive as a Predictive Analyst, and why are they important?

To thrive as a Predictive Analyst, you need a strong background in statistics, data analysis, and a relevant degree such as mathematics, computer science, or economics. Proficiency with data analytics tools like Python, R, SQL, and machine learning platforms, as well as familiarity with data visualization software, is typically required. Strong problem-solving abilities, critical thinking, and effective communication skills help you translate complex data findings into actionable business insights. These skills and qualifications are essential for delivering accurate forecasts that drive strategic decision-making and business growth.

How does a Predictive Analyst typically collaborate with other teams within an organization?

Predictive Analysts often work closely with cross-functional teams such as marketing, product management, and IT. They translate complex data findings into actionable insights for business decision-makers, requiring strong communication skills and the ability to present data visually. Collaboration may involve regular meetings to define project goals, share progress, and refine predictive models based on team feedback. This interdepartmental cooperation ensures that analytics align with overall business strategies and deliver measurable value.

What is a Predictive Analyst?

A Predictive Analyst is a professional who uses data analysis, statistical techniques, and machine learning models to forecast future outcomes and trends for a business or organization. They collect and interpret large sets of data to identify patterns and make predictions that help guide strategic decisions. Predictive Analysts often work with various software tools and collaborate with other departments to improve business performance and anticipate future challenges or opportunities.

What is the difference between Predictive Analyst vs Data Analyst?

AspectPredictive AnalystData Analyst
Required CredentialsBachelor's in Statistics, Data Science, or related field; often certifications in predictive modelingBachelor's in Data Analysis, Statistics, or related field; certifications in data visualization or analysis tools
Work EnvironmentAnalytical teams, data science departments, often in tech, finance, or healthcareBusiness units, reporting teams, across various industries
Employer & Industry UsageUsed in industries requiring forecasting and predictive modeling, like finance, marketing, healthcareUsed broadly for data reporting, visualization, and descriptive analysis across industries

Predictive Analysts focus on building models to forecast future trends using statistical and machine learning techniques, while Data Analysts primarily interpret existing data to generate reports and insights. Both roles require strong analytical skills, but Predictive Analysts typically have more specialized training in predictive modeling and data science tools.

More about Predictive Analyst jobs
What cities are hiring for Predictive Analyst jobs? Cities with the most Predictive Analyst job openings:
What states have the most Predictive Analyst jobs? States with the most job openings for Predictive Analyst jobs include:
What job categories do people searching Predictive Analyst jobs look for? The top searched job categories for Predictive Analyst jobs are:
Predictive Analyst jobs near you
Infographic showing various Predictive Analyst job openings in the United States as of June 2026, with employment types broken down into 4% Locum Tenens, 1% As Needed, 70% Full Time, 13% Part Time, 11% Contract, and 1% Nights. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $95,616 per year, or $46 per hour.

Predictive Analytics Fellow, Workforce Intelligence

AlphaHire

Remote

Contractor

Posted 13 days ago

Job description

About AlphaHire Workforce Intelligence Lab (WIL)
The AlphaHire Workforce Intelligence Lab (WIL) is an applied workforce research initiative focused on construction labor markets, workforce planning systems, compensation intelligence, labor scarcity analysis, and operational workforce visibility.
WIL develops workforce intelligence frameworks and regional labor market analysis designed to support operational decision-making across the construction industry.
The lab synthesizes publicly available labor data, compensation trends, contractor growth indicators, workforce demand signals, and construction activity into workforce intelligence systems for construction firms and industry operators.
Learn more:
AlphaHire Workforce Intelligence Lab (WIL)
About the role
We are seeking Predictive Analytics Fellows interested in workforce forecasting support systems, labor market analytics, operational workforce modeling, and workforce intelligence initiatives focused on the construction industry.
This fellowship is designed for graduate students, PhD candidates, analysts, data scientists, operations researchers, and analytically oriented professionals interested in workforce systems, labor market visibility, workforce planning, compensation analysis, and operational forecasting support.
Predictive Analytics Fellows will contribute to workforce intelligence initiatives focused on:
  • workforce trend modeling
  • labor market analytics
  • compensation trend analysis
  • workforce forecasting support
  • labor scarcity indicators
  • workforce intelligence methodologies
  • operational workforce visibility
  • workforce planning systems
  • workforce signal interpretation
  • dashboard validation
  • regional workforce intelligence reporting

This is a flexible, remote, project-based fellowship structured around approximately 3-5 hours per week.
Requirements
  • Support workforce intelligence and workforce forecasting initiatives
  • Assist with workforce analytics and labor market trend analysis
  • Contribute to workforce intelligence reports and publications
  • Participate in workforce intelligence framework and forecasting support development
  • Research publicly available labor market and workforce datasets
  • Support operational workforce visibility and workforce planning initiatives
  • Assist with dashboard validation and workforce signal analysis
  • Contribute to workforce intelligence methodology documentation
  • Support workforce forecasting support systems focused on operational construction decision-making

Preferred backgrounds
We are particularly interested in candidates with backgrounds in:
  • predictive analytics
  • workforce analytics
  • operations research
  • econometrics
  • statistics
  • industrial engineering
  • labor economics
  • forecasting systems
  • data science
  • business analytics
  • operational analytics
  • quantitative modeling
  • applied economics
  • mathematics
  • data analytics

Graduate students, PhD candidates, early-career researchers, analysts, and analytically oriented professionals are encouraged to apply.
Benefits
Fellowship structure
  • Flexible remote participation
  • Approximately 3-5 hours per week
  • Project-based collaboration
  • Ongoing contribution opportunities based on interest and availability

Additional information
This is an applied workforce analytics fellowship focused on operational workforce visibility and workforce planning support for the construction industry.
The fellowship is intended for individuals interested in:
  • workforce forecasting support systems
  • workforce analytics
  • labor market analysis
  • operational workforce systems
  • workforce intelligence methodologies
  • compensation intelligence
  • labor scarcity interpretation
  • workforce planning frameworks
  • construction workforce intelligence

rather than speculative forecasting or purely theoretical modeling.
The fellowship emphasizes:
  • explainable methodologies
  • operational usefulness
  • workforce visibility
  • practical workforce planning support
  • labor market interpretation

NOT:
  • black-box prediction systems
  • exaggerated AI claims
  • speculative forecasting
  • unsupported predictive precision

Benefits
What fellows receive
Predictive Analytics Fellows will have opportunities to:
  • contribute to workforce intelligence reports and publications
  • participate in applied workforce analytics initiatives
  • gain exposure to workforce planning systems and labor market analysis
  • contribute to workforce intelligence methodologies and forecasting support systems
  • build portfolio-quality workforce intelligence and analytics projects
  • collaborate on workforce intelligence dashboards and workforce visibility systems
  • participate in workforce intelligence discussions with researchers, analysts, and industry operators

As WIL expands, fellows may also have opportunities to participate in:
  • expanded research collaborations
  • advisory initiatives
  • future grant-supported projects
  • workforce intelligence publications and presentations
  • workforce forecasting and workforce planning initiatives

Apply