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How much do senior healthcare data science jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for senior healthcare data science in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What is the difference between Senior Healthcare Data Science vs Healthcare Data Analyst?

AspectSenior Healthcare Data ScienceHealthcare Data Analyst
Required CredentialsAdvanced degrees (Master's/PhD), experience in data science, programming skillsBachelor's degree, proficiency in data analysis tools, basic statistical knowledge
Work EnvironmentCross-functional teams, research projects, predictive modelingData reporting, data cleaning, basic analysis in healthcare settings
Employer & Industry UsageHospitals, healthcare tech companies, research institutionsClinics, insurance companies, healthcare providers
Common Search & Comparison IntentUnderstanding senior-level roles, qualifications, responsibilitiesEntry to mid-level analysis tasks, data reporting roles

Senior Healthcare Data Scientists focus on advanced analytics, predictive modeling, and developing algorithms, often requiring higher education and specialized skills. Healthcare Data Analysts perform routine data reporting and basic analysis. While both roles work within healthcare, they differ in complexity, responsibilities, and required expertise.

What is a Senior Healthcare Data Scientist?

A Senior Healthcare Data Scientist is an experienced professional who analyzes complex health-related data to improve patient outcomes, healthcare operations, and decision-making. They use advanced statistical methods, machine learning, and data modeling to interpret medical records, clinical trial results, insurance claims, and other healthcare data sources. In addition to technical expertise, they often collaborate with clinicians, administrators, and IT teams to implement data-driven solutions and support evidence-based practices. Their work helps healthcare organizations optimize care delivery, reduce costs, and advance medical research.

What are some common challenges faced by Senior Healthcare Data Scientists when working with clinical data?

Senior Healthcare Data Scientists often navigate challenges such as integrating data from diverse sources, ensuring data quality, and maintaining patient privacy in compliance with regulations like HIPAA. Dealing with incomplete or inconsistent electronic health records can be time-consuming, requiring strong data cleaning and validation skills. Collaboration with clinicians and IT teams is essential to accurately interpret data and translate findings into actionable insights for patient care and strategic decision-making.

What are the key skills and qualifications needed to thrive as a Senior Healthcare Data Scientist, and why are they important?

To thrive as a Senior Healthcare Data Scientist, you need advanced expertise in statistics, machine learning, and healthcare analytics, typically supported by a master's or PhD in a quantitative field. Mastery of tools like Python, R, SQL, and familiarity with healthcare data standards and cloud platforms is essential. Strong problem-solving, communication, and leadership skills help drive impactful solutions and bridge the gap between technical teams and healthcare stakeholders. These abilities are critical for generating actionable insights, improving patient outcomes, and ensuring data-driven decision-making in complex healthcare environments.
More about Senior Healthcare Data Science jobs
What cities are hiring for Senior Healthcare Data Science jobs? Cities with the most Senior Healthcare Data Science job openings:
What are the most commonly searched types of Healthcare Data Science jobs? The most popular types of Healthcare Data Science jobs are:
What states have the most Senior Healthcare Data Science jobs? States with the most job openings for Senior Healthcare Data Science jobs include:
What job categories do people searching Senior Healthcare Data Science jobs look for? The top searched job categories for Senior Healthcare Data Science jobs are:
Senior Healthcare Data Science jobs near you
Infographic showing various Senior Healthcare Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.
Senior Health Data Analyst I

Senior Health Data Analyst I

Partnership HealthPlan of California

Fairfield, CA • On-site

$106K - $138K/yr

Other

Medical

Re-posted 27 days ago

Job description

Overview
The Senior Healthcare Data Analyst I contributes to the overall success of the organization by
developing analytic solutions that support activities related to health services utilization
management, care coordination, quality improvement and population health. Through analyzing
patient claims, member enrollment, and other data, the Senior Healthcare Data Analyst
participates in identifying progress, performance and opportunities for improvement on
programs, quality of care, patient experience, and other metrics. This position requires a
thorough understanding of healthcare data and workflows, combined with an extensive
experience working with large data sets, conducting data analysis, including standard statistical
software (SAS), and creating reports using Tableau.
Responsibilities
  • Works collaboratively with business partners, other analysts, and IT to gather and
    integrate data from disparate sources.
  • Responds to ad hoc data requests from business units and leadership
  • Assists in design and development of data collection strategies, aggregation, analysis,
    and reporting to ensure data integrity and enhance information value.
  • Participates in design and interpretation of data analyses; provides recommendations for
    improvement of data quality and reporting.
  • Helps build, manage, and/or enhance predictive models
  • Assesses reporting and automation requirements and develops appropriate solutions.
  • Maintains in-depth knowledge of health plan operations, including claims processing,
    utilization management, quality improvement activities and pay for performance programs.
  • Critically analyzes data, draws conclusions and effectively articulates results.
  • Presents data and conclusions to non-technical audience; uses data visualizations and
    summaries to highlight key findings.
  • Creates and maintains thorough and consistent documentation of programs used to
    create reports.
  • Manages and prioritizes workload while meeting deliverables and expectations.
  • Works autonomously and collaboratively with report requestors, providing guidance to
    define report requirements and validate results.
  • Works collaboratively across departments to understand and meet the organization's
    analytic needs.

SECONDARY DUTIES AND RESPONSIBILITIES
  • Performs other assigned or needed activities required to assure success of the
    organization.
  • Participates in special projects as needed.
  • Performs other duties as assigned.

General Traits
  • Passionate about data, willing to acquire new skills and knowledge, flexible, self-motivated, and very curious.
  • Creative problem-solver, critical thinker, independent worker, data-driven mentality.
  • Communicates clearly and directly, relates well to others, engages people, provides and seeks feedback, articulates clearly, actively listens.

Qualifications
Education and Experience
Bachelor's degree with concentration in health informatics, health administration, public health, computing, epidemiology, statistics or related field, Master's degree preferred. Minimum four (4) years of
experience in data analysis and reporting. Knowledge of major health plan operations: healthcare claims processing, membership, provider, and benefits; or equivalent combination of education and experience.
Excellent knowledge of data collection, analysis, statistics and data presentation with experience in data mining techniques and procedures. Experience using statistical packages for analyzing large data sets, SAS and/or SQL a plus. Experience working with administrative data, ideally health care data (Medicaid data a plus). Understanding of health data formats including claims, lab and pharmacy. Knowledge of clinical coding systems (e.g., ICD9, ICD10, CPT).
Special Skills, Licenses and Certifications
Proficiency in inferential and predictive statistical analysis. MS Office, Excel, SQL, SAS, Tableau.
Ability to present complex information in an understandable and compelling manner.
Performance Based Competencies
Ability to quickly acquire in-depth knowledge of various systems related to claims processing, membership, provider, and benefits at Partnership. Strong written and oral communication skills with ability to interpret and
understand technical requirements. Excellent analytical skills to troubleshoot and resolve data issues. Must be highly organized and proficient at multi-tasking. Must be willing and able to provide gracious assistance to users, providers, and other constituents of Partnership.
Work Environment And Physical Demands
More than 50% of work time is spent at a video display terminal.
All HealthPlan employees are expected to:
  • Provide the highest possible level of service to clients;
  • Promote teamwork and cooperative effort among employees;
  • Maintain safe practices; and
  • Abide by the HealthPlan's policies and procedures, as they may from time to time be updated.

HIRING RANGE:
$106,667.05 - $138,667.16
IMPORTANT DISCLAIMER NOTICE
The job duties, elements, responsibilities, skills, functions, experience, educational factors and the requirements and conditions listed in this job description are representative only and not exhaustive or definitive of the tasks that an employee may be required to perform. The employer reserves the right to revise this job description at any time and to require employees to perform other tasks as circumstances or conditions of its business, competitive considerations, or work environment change.

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