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Health Data Analytics Jobs in Virginia (NOW HIRING)

Experience supporting HHS, NIH, FDA, CMS, CDC, or other health-focused federal environments ... Additional cloud, data, analytics, AI/ML, cybersecurity, Agile, ITIL, DAMA, CDMP, or project ...

Sr. Manager Data Analytics

Leesburg, VA ยท On-site

$150K - $170K/yr

Sr. Manager, Data & Analytics Location: Leesburg, VA (hybrid) Company: VB Spine Looking for a ... Comprehensive health, dental, and vision insurance * 401(k) with company match * Paid time off (PTO ...

As a healthcare analyst, you will be performing research/analysis based on the client data followed by contribution in internal projects. On the whole your going to be a passionate player in using ...

As a healthcare analyst, you will be performing research/analysis based on the client data followed by contribution in internal projects. On the whole your going to be a passionate player in using ...

Showing results 21-40

Health Data Analytics information

See Virginia salary details

$24

$54

$93

How much do health data analytics jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for health data analytics in Virginia is $54.28, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $61.49 per hour, depending on experience, location, and employer.

What is health data analytics?

Health data analytics is the process of examining large sets of healthcare data to uncover patterns, trends, and insights that can help improve patient outcomes and healthcare operations. Professionals in this field use statistical, computational, and analytical methods to interpret data from electronic health records, clinical trials, claims, and other sources. The goal is to support evidence-based decision making, optimize resource allocation, and enhance the quality of care. Health data analysts often work in hospitals, research institutions, insurance companies, and public health organizations.

What are the key skills and qualifications needed to thrive as a health data analyst?

To thrive as a Health Data Analyst, you need a solid background in statistics, data analysis, and health informatics, often supported by a degree in a related field such as public health, statistics, or computer science. Proficiency with analytical tools like SQL, Python, R, and healthcare data systems (e.g., EHRs, HL7) is typically required, and certifications like Certified Health Data Analyst (CHDA) can be advantageous. Strong problem-solving abilities, attention to detail, and effective communication skills help translate complex data into actionable healthcare insights. These skills enable analysts to improve patient outcomes, support decision-making, and drive efficiency within healthcare organizations.

What are some common challenges faced by professionals working in health data analytics, and how can they be managed?

Professionals in Health Data Analytics often encounter challenges such as managing large volumes of sensitive patient data, ensuring data privacy and compliance with regulations like HIPAA, and integrating data from multiple sources with varying formats and quality. Addressing these issues requires strong technical skills, attention to detail, and collaboration with IT, clinical, and compliance teams. Continuous learning about new analytics tools and regulatory changes also helps professionals stay effective and maintain data integrity.

What is the difference between Health Data Analytics vs Health Data Analysis?

AspectHealth Data AnalyticsHealth Data Analysis
Required SkillsData analysis, statistical skills, knowledge of healthcare dataData interpretation, statistical skills, healthcare knowledge
Tools & SoftwareAnalytics platforms, programming languages (Python, R)Excel, statistical software, visualization tools
Work EnvironmentData teams, healthcare organizations, research institutionsHealthcare providers, research settings, hospitals
FocusExtracting insights from large datasets, predictive modelingInterpreting data results, reporting findings

Health Data Analytics involves using advanced tools and techniques to extract insights from large healthcare datasets, often focusing on predictive modeling and data-driven decision-making. Health Data Analysis emphasizes interpreting healthcare data to inform clinical or operational decisions, typically involving statistical analysis and reporting. Both roles require healthcare knowledge and analytical skills but differ mainly in scope and complexity.

What are popular job titles related to Health Data Analytics jobs in Virginia? For Health Data Analytics jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Health Data Analytics jobs in Virginia look for? The top searched job categories for Health Data Analytics jobs in Virginia are:
What cities in Virginia are hiring for Health Data Analytics jobs? Cities in Virginia with the most Health Data Analytics job openings:
Infographic showing various Health Data Analytics job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $112,896 per year, or $54.3 per hour.

Pega Data Analytics Engineer

Compass Pointe Consulting

Vienna, VA โ€ข On-site

$114K - $138K/yr

Contractor

Medical, Dental, Vision, Life, Retirement

Re-posted 28 days ago


Job description


Senior Data Analytics Engineer - Pega CDH / Databricks
Position Overview
We are seeking a highly analytical and technically skilled Senior Data Analytics Engineer to support the development, implementation, and monitoring of advanced Customer Decision Hub (CDH) modeling capabilities. This role will focus on enabling faster analysis, improving data accessibility, and standardizing analytical processes across enterprise marketing and analytics teams.
The ideal candidate will have strong experience working within Databricks environments using Python/PySpark and SQL, along with expertise in large-scale data analysis, model performance monitoring, and customer interaction analytics. Experience with Pega Customer Decision Hub (Pega CDH) is strongly preferred.
This position will partner closely with analytics, modeling, marketing, and decisioning teams to create scalable analytical frameworks, reusable notebooks, and actionable monitoring solutions that improve customer engagement and model effectiveness.
Key Responsibilities
  • Develop and maintain a library of reusable queries, scripts, and analytical assets to replicate CDH customer contextual objects within external analytical platforms such as Databricks and ASL.
  • Standardize analytical processes and data retrieval methodologies for broader team usage and consistency.
  • Build scalable data pipelines and analytical frameworks using Python/PySpark and SQL.
  • Create reusable Databricks notebooks that enable self-service analytics across multiple business functions.
  • Develop standardized analytical solutions for interaction-to-outcome attribution analysis, model-to-interaction mapping, predictor performance tracking, member profile mapping, distribution analysis, arbitration analysis, and channel engagement analysis.
  • Support implementation and analysis of new model-related capabilities and features.
  • Establish baseline KPIs and monitoring frameworks for new modeling initiatives.
  • Design and support back-testing methodologies for model enhancements and propensity threshold analysis.
  • Monitor model maturity, performance trends, and operational effectiveness.
  • Develop near real-time monitoring approaches to identify low propensity scores, ineffective actions, and engagement gaps.
  • Improve visibility into model health and Next Best Interaction (NBI) program effectiveness.
  • Design analytical frameworks for eligible audience monitoring and treatment analysis.
  • Correlate interactions with demographic and behavioral data for deeper customer insights.

Required Qualifications
  • Bachelor's degree in Computer Science, Data Analytics, Information Systems, Mathematics, Statistics, or related field (or equivalent experience)
  • Strong hands-on experience with Databricks environments
  • Advanced proficiency in Python, PySpark, and SQL
  • Experience building reusable analytical frameworks and notebooks
  • Experience performing large-scale data analysis and data modeling
  • Strong understanding of model performance monitoring and KPI development
  • Ability to translate business questions into scalable analytical solutions

Preferred Qualifications
  • Experience with Pega Customer Decision Hub (Pega CDH)
  • Experience supporting marketing analytics, customer engagement, or decisioning platforms
  • Familiarity with propensity models, arbitration logic, and customer interaction analytics
  • Experience with monitoring frameworks and real-time analytical alerting
  • Understanding of customer journey analytics and Next Best Action/Interaction programs
  • Experience working in enterprise analytics or customer intelligence environments

Key Skills
Databricks, Python, PySpark, SQL, Data Engineering, Data Analytics, Model Monitoring, KPI Development, Customer Analytics, Predictive Modeling, Marketing Analytics, Notebook Development, Data Standardization, Decisioning Analytics, Stakeholder Collaboration
Success Metrics
  • Creation of reusable and scalable analytical assets for enterprise use
  • Reduction in time required to conduct CDH and model analysis
  • Improved visibility into model health and customer engagement effectiveness
  • Increased consistency and repeatability of analytical processes
  • Enhanced ability for teams to perform self-service analytics and monitoring

We offer Medical, Dental, Vision, Basic Life, Short-Term Disability, Accident, Term Life, Whole Life, and 401k for all W2 Consultants. A benefit overview will be provided as requested.