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Healthcare Data Science Jobs (NOW HIRING)

Curant Health

Healthcare Data Analyst

Smyrna, GA

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 ...

BerryDunn

Senior Healthcare Data Analyst

$88K - $111K/yr

Our team brings together deep expertise in health economics, actuarial science, data science, policy analysis, and advanced analytics to help clients address complex questions involving healthcare ...

WellSky

Data Scientist

Overland Park, KS · On-site

The Data Scientist is responsible for turning unstructured healthcare data into standardized, analysis-ready assets that power Life Sciences and RWE use cases. Working within the internal data ...

SteerBridge

Data Scientist

Vienna, VA · On-site

$137K - $155K/yr

Perform exploratory data analysis and feature engineering on claims, clinical, and healthcare ... Bachelor's degree in Applied Mathematics, Statistics, Computer Science, Data Science, or related ...

SteerBridge

Data Scientist

Vienna, VA

$137K - $155K/yr

Perform exploratory data analysis and feature engineering on claims, clinical, and healthcare ... Bachelor's degree in Applied Mathematics, Statistics, Computer Science, Data Science, or related ...

Scalepex

Healthcare Data Analyst

Dallas, TX · Remote

About the Role The Data Analyst plays a key role in monitoring, managing, and improving healthcare data file exchanges across clients, vendors, and internal systems. This role sits within a DataOps ...

Scalepex

Healthcare Data Analyst

Dallas, TX

About the Role The Data Analyst plays a key role in monitoring, managing, and improving healthcare data file exchanges across clients, vendors, and internal systems. This role sits within a DataOps ...

1 point system

Healthcare Data Engineer

New York, NY · Remote

$117K - $140K/yr

Master's or Bachelor's degree in Engineering (IT, Electronics, Communication, Computer Science, or ... Experience with healthcare data and health forms. Analytics: Experience in advanced analytics.

Pwc

Payer Healthcare Data Scientist, Manager

Denver, CO

$99K - $232K/yr

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

Pwc

Payer Healthcare Data Scientist, Manager

Seattle, WA

$99K - $232K/yr

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

Pwc

Payer Healthcare Data Scientist, Manager

Dallas, TX

$99K - $232K/yr

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

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Healthcare Data Science information

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$46K

$165K

$243.5K

How much do healthcare data science jobs pay per year?

As of Sep 2, 2026, the average yearly pay for healthcare data science in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is healthcare data science?

Healthcare data science is a field that uses data analysis, statistics, and machine learning to extract insights from health-related data. Professionals in this area work with large datasets from sources like electronic health records, clinical trials, and wearable devices. Their goal is to improve patient outcomes, optimize hospital operations, and support medical research by turning raw data into actionable information. This field requires knowledge of healthcare systems, data management, and advanced analytics techniques.

What are the key skills and qualifications needed to thrive as a healthcare data scientist?

To thrive as a Healthcare Data Scientist, you need a strong background in statistics, data analysis, programming (Python or R), and an understanding of healthcare systems, often supported by a degree in data science, computer science, or a related field. Experience with tools like SQL, machine learning frameworks, and familiarity with electronic health record (EHR) systems are typically required. Strong problem-solving skills, attention to detail, and effective communication help translate complex data insights into actionable healthcare solutions. These skills are crucial for deriving meaningful insights from complex healthcare data, improving patient outcomes, and supporting evidence-based decision-making.

What are some common challenges faced by healthcare data scientists when working with clinical data?

Healthcare data scientists often navigate challenges such as dealing with incomplete or inconsistent medical records, ensuring patient privacy and data security, and integrating data from diverse sources like electronic health records, lab results, and imaging systems. Additionally, they must collaborate closely with clinicians and IT staff to interpret complex datasets accurately and ensure that their analyses have practical clinical value. Maintaining compliance with healthcare regulations, such as HIPAA, is also a critical aspect of the role.

What is the difference between Healthcare Data Science vs Healthcare Data Analysis?

AspectHealthcare Data ScienceHealthcare Data Analysis
Required CredentialsTypically requires a degree in data science, statistics, or related fields; often includes programming skills and knowledge of machine learningUsually requires a background in healthcare, statistics, or data analysis; may include certifications in data analysis tools
Work EnvironmentInvolves developing models, algorithms, and predictive analytics; often in research or tech-focused settingsFocuses on interpreting data, generating reports, and supporting clinical or administrative decisions
Employer & Industry UsageUsed by healthcare tech companies, research institutions, and large healthcare providersCommon in hospitals, clinics, insurance companies, and healthcare consulting firms

Healthcare Data Science and Healthcare Data Analysis share overlapping skills but differ mainly in scope. Data scientists develop advanced models and predictive tools, while data analysts focus on interpreting data and generating insights. Both roles are vital in healthcare but serve different functions within the industry.

Can a healthcare data scientist work in healthcare?

Yes, healthcare data scientists work within healthcare organizations to analyze medical data, improve patient outcomes, and optimize operational efficiency. They often use tools like Python, R, and SQL, and require knowledge of healthcare systems, data privacy regulations, and statistical methods.

What can you do with a degree in healthcare data science?

A degree in healthcare data science prepares individuals for roles such as healthcare data analyst, data scientist, or informaticist, where they analyze medical data, develop predictive models, and improve patient outcomes. Skills in programming, statistics, and knowledge of healthcare systems are essential, and familiarity with tools like Python, R, and electronic health records is often required.
More about Healthcare Data Science jobs

What cities are hiring for Healthcare Data Science jobs?

Cities with the most 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 Healthcare Data Science jobs?

States with the most job openings for Healthcare Data Science jobs include:

What job categories do people searching Healthcare Data Science jobs look for?

The top searched job categories for Healthcare Data Science jobs are:

Healthcare Data Science jobs near you
Infographic showing various Healthcare Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Healthcare Data Analyst

Curant Health

Smyrna, GA

Full-time

Posted 21 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.

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