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Healthcare Data Analytics Jobs in Georgia (NOW HIRING)

... operational analytics for an assigned Rare program. This role is responsible for recurring ... with data, and interested in developing their career in healthcare analytics and business ...

Understanding of healthcare data such as claims data, sales data, pharmacy sales data etc. * Hands-on experience in data aggregation and analysis using Python, SQL or similar * Prior experience with ...

Manager, Data Analytics

Atlanta, GA · Hybrid

$111K - $145K/yr

... healthcare, finance or the insurance industry Bonus points: * 2+ years experience in preparing healthcare analytics, reporting, and data management * Experience with ticketing system (such as Jira)

Manager, Data Analytics

Atlanta, GA · On-site

$111K - $145K/yr

We're hiring a Data Analytics Manager to join our Operations Team. Oscar is the first health ... We're on a mission to change health care -- an experience made whole by our unique backgrounds and ...

Manager, Data Analytics

Atlanta, GA · On-site

$111K - $145K/yr

We're hiring a Data Analytics Manager to join our Operations Team. Oscar is the first health ... We're on a mission to change health care -- an experience made whole by our unique backgrounds and ...

Manager, Data Analytics

Atlanta, GA · Hybrid

$111K - $145K/yr

We're hiring a Data Analytics Manager to join our Operations Team. Oscar is the first health ... We're on a mission to change health care -- an experience made whole by our unique backgrounds and ...

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Healthcare Data Analytics information

See Georgia salary details

$20

$46

$79

How much do healthcare data analytics jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for healthcare data analytics in Georgia is $46.23, according to ZipRecruiter salary data. Most workers in this role earn between $37.16 and $52.36 per hour, depending on experience, location, and employer.

What is a healthcare data analytics?

A Healthcare Data Analytics job involves collecting, processing, and analyzing healthcare data to improve patient outcomes, operational efficiency, and decision-making. Professionals in this role use statistical models, machine learning, and data visualization tools to identify trends and insights. They work with electronic health records (EHRs), claims data, and other medical datasets to support healthcare providers, insurers, and policymakers. This role requires knowledge of data analysis techniques, healthcare regulations (such as HIPAA), and industry-specific software.

What are the key skills and qualifications needed to thrive in healthcare data analytics?

To thrive in Healthcare Data Analytics, you need a strong background in statistics, data analysis, and healthcare systems, often supported by a degree in health informatics, data science, or a related field. Experience with tools like SQL, Python/R, Tableau, and electronic health record (EHR) systems, as well as certifications such as Certified Health Data Analyst (CHDA), is highly valuable. Problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and present insights to non-technical stakeholders. These competencies are crucial for successfully leveraging data to improve patient outcomes and drive operational efficiencies in healthcare organizations.

What are some typical challenges faced in a healthcare data analytics role?

Healthcare Data Analytics professionals often encounter challenges such as dealing with incomplete or inconsistent data, ensuring compliance with strict data privacy regulations like HIPAA, and integrating data from multiple sources. Maintaining data integrity while extracting meaningful insights requires analytical rigor and a thorough understanding of both healthcare workflows and data management best practices. Additionally, translating complex findings into actionable recommendations for clinical or administrative teams can be demanding but is key to driving improvements. Effective communication and a proactive approach to problem-solving help address these challenges and ensure impactful results.

How do I become a healthcare data analyst?

To become a healthcare data analyst, you typically need a bachelor's degree in health informatics, statistics, or a related field. Developing skills in data analysis tools like Excel, SQL, and statistical software, along with understanding healthcare data and regulations, is essential. Gaining experience through internships or certifications such as Certified Health Data Analyst (CHDA) can also improve job prospects.

Is healthcare data analytics a good career?

Healthcare data analytics is a growing field that involves analyzing health data to improve patient outcomes and operational efficiency. It typically requires skills in data management, statistical analysis, and familiarity with tools like SQL and Python, with certifications such as Certified Health Data Analyst (CHDA) enhancing job prospects. The role offers strong job growth, competitive salaries, and opportunities across healthcare providers, insurance companies, and technology firms.

What does a healthcare data analyst do in healthcare?

A healthcare data analyst collects, analyzes, and interprets healthcare data to improve patient outcomes, optimize operations, and support decision-making. They use tools like Excel, SQL, and data visualization software to identify trends and generate reports for healthcare providers and administrators.

What are popular job titles related to Healthcare Data Analytics jobs in Georgia?

For Healthcare Data Analytics jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Healthcare Data Analytics jobs in Georgia look for?

The top searched job categories for Healthcare Data Analytics jobs in Georgia are:

What cities in Georgia are hiring for Healthcare Data Analytics jobs?

Cities in Georgia with the most Healthcare Data Analytics job openings:

Infographic showing various Healthcare Data Analytics job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 11% Part Time, 7% Contract, and 3% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $96,153 per year, or $46.2 per hour.

Full-time

Posted 8 days ago


Job description

Position Summary

The Data Analyst I – Curant Rare supports Curant Health’s manufacturer-facing reporting and operational analytics for an assigned Rare program. This role is responsible for recurring reporting, Power BI dashboard support, data validation, KPI and SLA monitoring, and analysis used in operational reviews and Quarterly Business Reviews (QBRs).

The Data Analyst I works with patient, referral, prior authorization, dispensing, and workflow data to provide accurate and actionable insights to program leadership and cross-functional partners. This position also partners with internal teams and client data contacts to investigate reporting questions, resolve data discrepancies, and ensure reporting deliverables are accurate, timely, and aligned with business requirements.

The ideal candidate is analytical, detail-oriented, comfortable working with data, and interested in developing their career in healthcare analytics and business intelligence.

Duties and Responsibilities

Core duties and responsibilities include the following. Other duties may be assigned based on business and program needs.

Reporting and Dashboard Management
  • Maintain, refresh, validate, and support Power BI reports and operational dashboards.
  • Produce daily, weekly, monthly, and quarterly reporting for program leadership and manufacturer reviews.
  • Monitor key program metrics, including referral volume, patient onboarding, benefit verification, prior authorization, dispensing, conversion, adherence, persistence, workflow activity, and service-level performance.
  • Create clear visualizations, scorecards, trends, and patient-level detail views that support operational decision-making.
  • Maintain documentation for report logic, source fields, refresh cadence, filters, exclusions, and known data limitations.
Data Quality, Reconciliation, and Validation
  • Validate reporting outputs against source systems and established business rules before distribution.
  • Reconcile patient counts, status classifications, dates, and KPI results across reports and reporting periods.
  • Identify potential data-quality issues and assist with investigating root causes.
  • Document reporting exceptions and coordinate with business and technical partners to support resolution.
  • Maintain organized validation files, metric definitions, and reporting documentation.
  • Escalate significant data discrepancies or reporting concerns appropriately.
Business Analysis and Operational Insights
  • Analyze patient journeys and operational workflows to identify trends and potential barriers to enrollment, therapy initiation, conversion, and refill continuity.
  • Evaluate performance across workflow steps, patient status, payer, aging, responsible party, and other relevant operational dimensions.
  • Support cohort, trend, aging, turnaround-time, and exception analysis.
  • Translate analytical findings into clear summaries for program leadership and business partners.
  • Assist with ad hoc reporting and analysis requests while maintaining consistent documentation and methodology.
QBR, Manufacturer, and Cross-Functional Support
  • Prepare validated data, exhibits, supporting details, and commentary for monthly operational reviews and Quarterly Business Reviews.
  • Partner with Patient Engagement, Pharmacy, Finance, IT, and program leadership to clarify reporting requirements and resolve reporting questions.
  • Maintain awareness of recurring reporting deadlines and support timely completion of deliverables.
  • Participate in requirements gathering, user acceptance testing, and implementation of approved report and dashboard enhancements.
Client Data Team Collaboration
  • Work with client data contacts to clarify reporting requirements and investigate data discrepancies.
  • Assist with resolving reporting, data-transfer, and data-alignment challenges.
  • Communicate findings, open questions, and proposed resolutions clearly and professionally with internal stakeholders and client contacts.
  • Track client-facing data issues and maintain appropriate documentation of findings, root causes, and follow-up actions.
  • Escalate unresolved reporting or data risks to program leadership as appropriate.
  • Support alignment between Curant reporting outputs and client reporting expectations.