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Predictive Analyst Jobs (NOW HIRING)

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Predictive Analyst information

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How much do predictive analyst jobs pay per hour?

As of Aug 18, 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 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 are the key skills and qualifications needed to thrive as a predictive analyst?

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 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.

How do you become a predictive analyst?

To become a predictive analyst, you typically need a bachelor's degree in fields like statistics, mathematics, or data science. Developing skills in programming languages such as Python or R, understanding machine learning techniques, and gaining experience with data analysis tools are essential. Earning certifications in data analytics or machine learning can also enhance job prospects.
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What cities are hiring for Predictive Analyst jobs?

Cities with the most Predictive Analyst job openings:

Who are the top companies hiring for Predictive Analyst jobs?

The top employers for Predictive Analyst jobs are:

What states have the most Predictive Analyst jobs?

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

Infographic showing various Predictive Analyst job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 5% Part Time, and 6% Contract. Highlights an 80% Physical, 9% Hybrid, and 11% Remote job distribution, with an average salary of $95,616 per year, or $46 per hour.

Full-time

Re-posted 22 hours ago


University Of Texas at Austin rating

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

126th of 618 rated colleges and universities


Job description

Job Posting Title:
Data Science Analyst II
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Hiring Department:
Dell Medical School
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Position Open To:
All Applicants
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Weekly Scheduled Hours:
40
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FLSA Status:
Exempt from FLSA
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Earliest Start Date:
Immediately
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Position Duration:
Expected to Continue
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Location:
UT MAIN CAMPUS
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Job Details:
Purpose
The Data Science Analyst II partners with clinical, operational, and administrative leaders to develop advanced analytics, predictive models, and decision-support solutions that improve patient care, operational efficiency, and organizational performance.
This role translates complex healthcare and business problems into scalable data science and machine learning solutions while collaborating closely with clinicians, informaticists, data engineers, and business stakeholders. The Data Science Analyst II develops predictive models, builds automated data pipelines, and delivers actionable insights that support enterprise decision-making and clinical innovation.
Responsibilities
Clinical & Operational Partnership
  • Partner directly with clinicians, operational leaders, researchers, and administrative stakeholders to identify analytical opportunities that improve patient care and operational performance.
  • Translate complex clinical and business questions into scalable analytical solutions.
  • Present technical findings and recommendations to both technical and non-technical audiences.
  • Serve as a trusted consultant on data science, predictive analytics, and AI initiatives.

Advanced Data Science & Predictive Modeling
  • Design, develop, validate, and deploy predictive and machine learning models supporting clinical and operational initiatives.
  • Perform feature engineering, model evaluation, hyperparameter tuning, and performance monitoring.
  • Conduct forecasting, trend analysis, anomaly detection, and scenario modeling.
  • Monitor deployed models for drift and recommend improvements as data changes.
  • Translate analytical findings into actionable recommendations.

Data Integration & Engineering
  • Build and maintain automated ETL pipelines and reproducible analytical workflows.
  • Integrate structured and unstructured data from multiple enterprise healthcare systems.
  • Ensure data quality through validation, reconciliation, and testing.
  • Partner with Data Engineering and IT teams to optimize data architecture and performance.

Visualization & Decision Support
  • Develop dashboards and interactive reporting tools that support operational and clinical decision-making.
  • Automate recurring reports and analytical processes.
  • Maintain consistency of KPIs and enterprise reporting standards.
  • Create clear visualizations that simplify complex analytical findings.

Project Leadership & Collaboration
  • Lead small-to-medium analytics initiatives from planning through implementation.
  • Define project milestones, manage priorities, and communicate status updates.
  • Mentor junior analysts and promote data science best practices.
  • Collaborate closely with data architects, engineers, informaticists, and clinical leaders to ensure successful implementation.

Marginal or Periodic Functions
  • Evaluate emerging AI, machine learning, and cloud technologies for enterprise adoption.
  • Monitor model performance and coordinate remediation following data or regulatory changes.
  • Ensure compliance with HIPAA, security standards, and institutional policies.
  • Adhere to internal controls and reporting requirements.
  • Perform related duties as assigned.

Knowledge, Skills & Abilities
Technical Expertise
  • Strong understanding of predictive analytics, statistics, and machine learning techniques.
  • Proficiency in Python, SQL, and modern analytics frameworks.
  • Experience developing automated ETL pipelines and maintaining data integrity.
  • Experience working with cloud-based analytics environments.

Communication
  • Ability to communicate technical concepts to clinical, operational, and executive audiences.
  • Strong presentation and stakeholder engagement skills.
  • Ability to translate complex analytical findings into actionable recommendations.

Collaboration
  • Demonstrated ability to partner effectively with clinicians, researchers, operational leaders, and technical teams.
  • Strong business acumen with a collaborative, solution-oriented approach.
  • Ability to balance technical feasibility with operational priorities.

Required Qualifications
  • Master's degree in Data Science, Statistics, Computer Science, Engineering, Health Informatics, or a related field, with at least three (3) years of professional experience in data science, predictive analytics, machine learning, or healthcare analytics.
  • Experience applying data science and predictive analytics to solve healthcare, clinical, or business problems.
  • Strong SQL, data modeling, and Python programming skills.
  • Experience developing ETL pipelines and working with cloud platforms (Azure, AWS, or Google Cloud).
  • Experience collaborating directly with business, operational, clinical, or research stakeholders to develop analytical solutions.
  • Excellent written, verbal, and interpersonal communication skills.
  • Relevant education and experience may be substituted as appropriate.
  • Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship.

Preferred Qualifications
  • Doctorate in Data Science, Computer Science, Engineering, Statistics, Health Informatics, or related field.
  • Five (5)+ years of applied machine learning or healthcare analytics experience.
  • Experience supporting provider organizations, academic medical centers, hospitals, or integrated health systems.
  • Experience working with provider-side healthcare data, clinical workflows, operational healthcare analytics, or population health initiatives.
  • Experience working with healthcare datasets and interoperability standards such as OMOP, FHIR, or HL7.
  • Experience operationalizing machine learning models using MLOps practices.
  • Experience developing automated ETL pipelines and cloud-native analytics solutions.

Salary
$80,000+ depending on qualifications.
Important Employment Requirement:
Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship. This position is not eligible for employment visa sponsorship.
Working Conditions
  • Standard office equipment
  • Repetitive use of a keyboard
  • May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.

Required Materials
  • Resume/CV
  • 3 work references with their contact information; at least one reference should be from a supervisor
  • Letter of interest

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
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E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university's company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
  • E-Verify Poster (English and Spanish) [PDF]
  • Right to Work Poster (English) [PDF]
  • Right to Work Poster (Spanish) [PDF]

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Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

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