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How much do remote predictive analytics jobs pay per year?

As of Sep 10, 2026, the average yearly pay for remote predictive analytics in the United States is $127,031.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $143,500.00 per year, depending on experience, location, and employer.

What is remote predictive analytics?

Remote predictive analytics jobs involve analyzing large datasets to identify patterns, trends, and future outcomes, all while working from a location outside of a traditional office. Professionals in these roles use statistical methods, machine learning, and data modeling to forecast business results and provide actionable insights. They often collaborate with teams virtually and use specialized software to process and interpret data. These positions are common in industries like finance, healthcare, marketing, and e-commerce where understanding future trends is crucial.

What skills and qualifications are needed for remote predictive analytics?

To thrive in Remote Predictive Analytics, you need a strong background in statistics, data analysis, and machine learning, typically supported by a relevant degree in data science, mathematics, or computer science. Familiarity with programming languages like Python or R, data visualization tools, and cloud-based analytics platforms is essential, along with certifications such as SAS, AWS, or Google Cloud. Strong problem-solving, communication, and time management skills help professionals effectively interpret data insights and collaborate remotely with stakeholders. These competencies are critical for delivering accurate, actionable predictions and driving data-informed decisions in distributed work environments.

How do remote predictive analytics professionals collaborate with cross-functional teams?

Remote predictive analytics professionals frequently collaborate with data engineers, business analysts, and stakeholders through virtual meetings and shared digital platforms. They often participate in agile workflows, leveraging collaboration tools like Slack, Jira, or Trello to coordinate tasks and share progress. Effective communication of complex findings to non-technical team members is a key challenge, so clear documentation and visualization tools are essential. Building strong relationships remotely requires proactive engagement and regular check-ins to ensure project alignment and timely delivery of analytics insights.
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Remote Predictive Analytics jobs near you
Infographic showing various Remote Predictive Analytics job openings in the United States as of September 2026, with employment types broken down into 11% Internship, 78% Full Time, and 11% Part Time. Highlights an 100% Remote job distribution, with an average salary of $127,031 per year, or $61.1 per hour.

Predictive Analytics Fellow, Workforce Intelligence

Remote

AlphaHire
See more jobs at AlphaHireexternal

Contractor

Re-posted 16 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