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Population Health Analytics Jobs (NOW HIRING)

St. Barnabas

Senior Population Health Analyst

Bronx, NY · On-site

$91K - $121K/yr

Under the direction of the Vice President, the Senior Population Health Analyst provides strategic, operational and managerial leadership to the department. They direct installation, configuration ...

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$117

$192

How much do population health analytics jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for population health analytics in the United States is $117.61, according to ZipRecruiter salary data. Most workers in this role earn between $58.17 and $192.31 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Population Health Analytics position, and why are they important?

To thrive in Population Health Analytics, you need strong analytical skills, experience with health data management, and a background in statistics, epidemiology, public health, or a related field. Proficiency with data analytics tools such as SQL, SAS, R, Python, and health informatics platforms, as well as certifications like Certified Health Data Analyst (CHDA), are highly valuable. Excellent communication, problem-solving abilities, and collaboration skills help translate data insights into actionable solutions within multidisciplinary healthcare teams. These competencies enable impactful data-driven decisions that improve patient outcomes and healthcare system performance.

What is a Population Health Analytics job?

A Population Health Analytics job involves analyzing healthcare and demographic data to identify trends, improve patient outcomes, and optimize healthcare resources. Professionals in this role use data science, statistics, and technology to assess health risks, evaluate interventions, and inform policy decisions. They often work with hospitals, insurance companies, government agencies, or research institutions to enhance public health strategies. Strong analytical skills, proficiency in data visualization tools, and a background in healthcare or public health are typically required for this role.

What are typical daily responsibilities of someone in Population Health Analytics?

Professionals in Population Health Analytics spend much of their day collecting, cleaning, and analyzing large sets of health data from hospitals, clinics, and public health sources. They also generate reports and visualizations to communicate findings, and work closely with clinicians, administrators, and IT teams to identify trends and opportunities for quality improvement. Interpreting complex data for non-technical stakeholders and making recommendations are central aspects of the role. This often involves balancing independent analysis time with team meetings and cross-departmental collaboration.

More about Population Health Analytics jobs
What states have the most Population Health Analytics jobs? States with the most job openings for Population Health Analytics jobs include:
What job categories do people searching Population Health Analytics jobs look for? The top searched job categories for Population Health Analytics jobs are:
Population Health Analytics jobs near you
Infographic showing various Population Health Analytics job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 93% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $244,631 per year, or $117.6 per hour.
Population Health Data Engineer

Population Health Data Engineer

Software Technology Inc

Saint Charles, MO • On-site

$107K - $129K/yr

Other

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

Job description

Population Health Data Engineer

We are seeking a skilled Population Health Data Engineer with deep expertise in Epic data ecosystems and healthcare analytics. This role will focus on designing, building, and optimizing data pipelines and models to support population health, quality of care and claims analytics.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines supporting population health, claims analytics, and reporting.
  • Work extensively with Epic data sources including Registries, Rosters, Chronicles, Clarity, and Caboodle.
  • Integrate clinical and claims data to support longitudinal patient views and advanced analytics.
  • Develop data models for population health use cases including quality measures, risk stratification, utilization, and care management analysis.
  • Support development and operationalization of risk scoring data models and analytics (e.g., MARA, HCC, RAF).
  • Process and transform healthcare claims data (medical and pharmacy) for analytics and reporting.
  • Work with Milliman MedInsight data structures to support payer-provider analytics and efficiency benchmarking.
  • Build and optimize ELT pipelines using modern cloud platforms.
  • Collaborate with healthy planet, efficiency, quality, clinical, and analytics teams to translate business needs into technical solutions.
  • Ensure data quality, governance, and compliance with healthcare regulations (e.g., HIPAA).
  • Optimize performance of large-scale datasets and queries.
Required Qualifications
  • Strong hands-on experience with Epic systems, including:
    • Epic Registries
    • Chronicles data structures
    • Hyperspace or Hyperdrive environments
    • Clarity and Caboodle data models
  • Experience with modern data engineering tools and platforms:
    • Snowflake (data warehousing)
    • DBT (data transformation and modeling)
    • Dynamic Tables in Snowflake
  • Solid understanding of healthcare domain concepts, including population health and value-based care.
  • Experience with healthcare claims processing (medical and pharmacy claims).
  • Hands-on experience with Milliman MedInsight data models and analytics workflows.
  • Strong SQL and data modeling expertise.
  • Experience building and maintaining data pipelines.
Key Skills
  • Population Health & Risk Analytics
  • Healthcare Data Modeling (Clinical and Claims)
  • Epic Data Ecosystem Expertise
  • Snowflake & DBT
  • SQL & Performance Optimization
  • Data Governance & Compliance
Education & Experience
  • Bachelor’s or Master’s degree in Computer Science, Health Informatics, Data Engineering, or related field.
  • 6+ years of experience in data engineering, with strong preference for healthcare, payer, or population health analytics experience.

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