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Senior Health Informatics Data Analyst Jobs (NOW HIRING)

Sr Health Data Analyst

Seattle, WA · On-site

$97K - $123K/yr

The Sr. Health Data Analyst will assist in the production of performance reports, specialized ... Candidates should have a Masters in Health Informatics, Health Administration, Public Health ...

Sr Health Data Analyst

Seattle, WA · On-site

$97K - $123K/yr

The Sr. Health Data Analyst will assist in the production of performance reports, specialized ... Candidates should have a Masters in Health Informatics, Health Administration, Public Health ...

Senior Healthcare Data Analyst

Washington, DC · On-site

$97K - $122K/yr

Healthcare Informatics Data Analyst Ponos Care is a physician‐driven healthcare organization ... This role will serve as the first dedicated, senior analytics hire, owning the full analytics ...

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Senior Health Informatics Data Analyst information

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$55K

$99.2K

$135.5K

How much do senior health informatics data analyst jobs pay per year?

As of Jun 5, 2026, the average yearly pay for senior health informatics data analyst in the United States is $99,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $108,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Health Informatics Data Analyst, and why are they important?

A Senior Health Informatics Data Analyst typically needs expertise in data analytics, healthcare data standards, and a background in health informatics, often supported by a relevant degree or certification such as Certified Health Data Analyst (CHDA). Proficiency in tools like SQL, Python, R, and healthcare information systems (e.g., EHRs, HL7, FHIR) is crucial for effective data management and analysis. Strong problem-solving, communication, and project management skills enable effective collaboration with clinical and IT teams. These competencies are essential for translating complex health data into actionable insights that drive improved patient outcomes and organizational efficiency.

How does a Senior Health Informatics Data Analyst typically collaborate with clinical and IT teams on healthcare projects?

A Senior Health Informatics Data Analyst frequently acts as a bridge between clinical staff and IT professionals. They translate clinical requirements into technical solutions by working closely with healthcare providers to understand their data needs and with IT teams to ensure proper data integration and system functionality. This role often involves leading cross-functional meetings, facilitating communication between departments, and ensuring that data-driven insights are actionable and align with organizational goals. Effective collaboration is essential to implement successful healthcare analytics projects and improve patient outcomes.

What does a Senior Health Informatics Data Analyst do?

A Senior Health Informatics Data Analyst is responsible for analyzing complex healthcare data to improve patient outcomes, optimize operations, and support decision-making within healthcare organizations. They work with electronic health records (EHR), clinical databases, and other health information systems to extract, clean, and interpret data. Their expertise helps identify trends, ensure data quality, and provide actionable insights for healthcare providers and administrators. In addition to technical skills, they often collaborate with clinicians and IT professionals to implement data-driven solutions. This role typically requires advanced knowledge of data analytics, healthcare systems, and regulatory compliance.

What is the difference between Senior Health Informatics Data Analyst vs Health Data Analyst?

AspectSenior Health Informatics Data AnalystHealth Data Analyst
Required CredentialsBachelor's or Master's in Health Informatics, Data Science, or related field; experience preferredBachelor's degree in Health Information Management, Data Science, or related field
Work EnvironmentHealthcare organizations, hospitals, clinics, or health tech companiesHealthcare providers, research institutions, or health insurance companies
Employer & Industry UsageUsed in healthcare settings for advanced data analysis and informatics projectsUsed for routine data reporting, analysis, and supporting clinical decision-making

The main difference is that Senior Health Informatics Data Analysts typically have more experience, advanced skills in health informatics, and handle complex projects, whereas Health Data Analysts focus on routine data analysis and reporting. Both roles are vital in healthcare data management but differ in scope and responsibility.

What cities are hiring for Senior Health Informatics Data Analyst jobs? Cities with the most Senior Health Informatics Data Analyst job openings:
What are the most commonly searched types of Health Informatics Data Analyst jobs? The most popular types of Health Informatics Data Analyst jobs are:
What states have the most Senior Health Informatics Data Analyst jobs? States with the most job openings for Senior Health Informatics Data Analyst jobs include:

Senior Health Informatics / Data Scientist

Inizio Partners

San Francisco, CA • Remote

Other

This job post has expired today. Applications are no longer accepted.


Job description

About the job Senior Health Informatics / Data Scientist
Role: Senior Health Informatics / Data Scientist
Location: Remote (U.S.)
Duration: 6+ Month Contract
Working Time Zone: PST (Pacific Time Zone)
Position Overview
We are seeking a Senior Health Informatics / Data Scientist with deep technical expertise in statistical modeling, machine learning, and healthcare data analytics. This is a hands-on role focused on developing data science models using Python to support risk stratification and risk tier migration initiatives within the U.S. healthcare ecosystem.
The ideal candidate will have experience working with healthcare claims and population health datasets, building predictive models that support patient risk identification and care management strategies. The role requires strong familiarity with Medicare, Medicaid, and other U.S. healthcare reimbursement structures and coding frameworks.
This individual will collaborate with analytics, clinical, and population health teams to develop models that help identify high-risk populations and support value-based care initiatives.
Key Responsibilities

  • Develop and implement statistical and machine learning models for healthcare risk stratification and population health analytics.
  • Build predictive models to support risk tier migration and risk adjustment strategies.
  • Use Python and modern data science libraries (pandas, NumPy, scikit-learn, etc.) to design, test, and deploy analytical models.
  • Analyze large-scale healthcare datasets including claims, clinical, and demographic data.
  • Work with healthcare stakeholders to translate analytical findings into actionable insights for care management and population health initiatives.
  • Identify high-risk patient cohorts and support targeted intervention strategies.
  • Ensure models and analytics align with Medicare, Medicaid, and other reimbursement frameworks.
  • Document methodologies and present insights to both technical and non-technical stakeholders.
Required Qualifications
  • Advanced degree in Data Science, Statistics, Biostatistics, Computer Science, Health Informatics, or related quantitative field.
  • Strong experience in statistical modeling, machine learning, and predictive analytics.
  • Hands-on Python programming experience for data science and model development.
  • Experience working with healthcare claims data, population health data, or clinical datasets.
  • Demonstrated experience with risk stratification, risk adjustment, or population health modeling.
  • Strong analytical and problem-solving skills.
Preferred Qualifications
  • Experience with risk tier migration analytics within healthcare organizations or health plans.
  • Familiarity with Medicare and Medicaid reimbursement structures.
  • Knowledge of healthcare coding standards such as ICD, CPT, and HCPCS codes.
  • Experience working with health plans, healthcare analytics firms, provider organizations, or consulting firms.