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Internship Healthcare Data Science Jobs in Washington

Healthcare Data Scientist

Washington, DC ยท On-site

$120 - $150/hr

Data Scientist - ATA, LLC ATA is seeking a Data Scientist to support data pipeline development ... The position will work extensively with healthcare data originating from EHR systems and interface ...

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 ...

Health Policy Data Scientist

Tysons, VA ยท On-site

$90K - $130K/yr

Analyze healthcare, compliance, and technical data to develop and maintain interactive reporting ... Bachelor's degree in Computer Science, Data Science, Information Systems, Data Analytics, or a ...

Data Scientist (Mid-Level)

Vienna, VA ยท 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 ...

Data Scientist (Mid-Level)

Vienna, VA ยท 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 ...

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 ...

New

Senior Data Scientist-RWE

Washington, DC ยท On-site

$126K - $158K/yr

In this role, you'll leverage advanced data science and health economics methods to help shape access to life-saving therapies and innovations. You'll work with rich, real-world healthcare data ...

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Internship Healthcare Data Science information

What is an internship in healthcare data science?

An internship in healthcare data science is a temporary position, often for students or recent graduates, that provides hands-on experience in analyzing and interpreting healthcare data. Interns typically work with professionals on projects involving data cleaning, statistical analysis, machine learning, and data visualization to support healthcare decision-making and improve patient outcomes. These internships help participants develop technical skills, gain industry knowledge, and build professional networks in the rapidly growing field of healthcare data science.

What are the key skills and qualifications needed to thrive as an internship in healthcare data science?

To thrive as an intern in healthcare data science, you need a solid grasp of statistics, data analysis, and programming languages such as Python or R, typically supported by coursework or a degree in data science, computer science, or a related field. Familiarity with data visualization tools (e.g., Tableau), healthcare databases (e.g., EHR systems), and knowledge of HIPAA regulations are often expected. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in this role. These capabilities are essential for transforming complex healthcare data into actionable insights that improve patient outcomes and support data-driven decision-making.

What types of projects do interns in healthcare data science typically work on, and how do these projects contribute to real-world healthcare improvements?

Interns in Healthcare Data Science often work on projects such as analyzing patient data to identify trends, developing predictive models for disease progression, or optimizing hospital resource allocation. These projects are usually part of larger, cross-functional teams including clinicians, IT specialists, and senior data scientists. The outcomes of your work can directly impact patient care processes, inform decision-making, and improve operational efficiency in healthcare settings. Expect regular mentorship and feedback, as well as opportunities to present your findings to technical and non-technical stakeholders.

What is the difference between Internship Healthcare Data Science vs Healthcare Data Analyst?

AspectInternship Healthcare Data ScienceHealthcare Data Analyst
Required CredentialsTypically pursuing or recent graduate in data science, statistics, or related fieldOften requires degree in health informatics, statistics, or related field
Work EnvironmentInternship setting, often in hospitals, healthcare tech companies, or research institutionsFull-time or part-time roles in healthcare organizations, clinics, or health IT firms
Employer & Industry UsageUsed by healthcare providers, research institutions, and tech companies for training and entry-level rolesCommon in hospitals, insurance companies, and healthcare consulting firms for data analysis tasks

Internship Healthcare Data Science positions are entry-level, focused on training and gaining experience in data science techniques applied to healthcare. Healthcare Data Analysts are more established roles, responsible for analyzing healthcare data to support decision-making. Both roles require similar educational backgrounds but differ in experience level and job responsibilities.

Can data science be used in healthcare?

Healthcare Data Science is a field that applies data analysis, machine learning, and statistical methods to improve patient outcomes, optimize operations, and support clinical decision-making. Data scientists in healthcare often work with electronic health records, medical imaging, and health-related datasets using tools like Python, R, and SQL. This role requires understanding healthcare regulations and data privacy standards such as HIPAA.

How do I become a healthcare data scientist?

To become a healthcare data scientist, you typically need a strong background in data science, statistics, or computer science, often with a relevant bachelor's or master's degree. Skills in programming languages like Python or R, knowledge of healthcare data systems, and experience with machine learning are essential. Gaining certifications in data analysis or healthcare informatics can also enhance your qualifications.

How to get an internship in healthcare data science?

To secure a healthcare data science internship, candidates should have a strong foundation in data analysis, programming (such as Python or R), and knowledge of healthcare systems. Relevant coursework, certifications in data science or healthcare analytics, and experience with tools like SQL and machine learning can improve chances. Applying through university career services, networking with industry professionals, and demonstrating project work are also effective strategies.

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

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

What cities in Washington are hiring for Internship Healthcare Data Science jobs?

Cities in Washington with the most Internship Healthcare Data Science job openings:

Infographic showing various Internship Healthcare Data Science job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Healthcare Data Scientist

Cherokee Federal

Washington, DC โ€ข On-site

$120 - $150/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Job description

Data Scientist - ATA, LLC

ATA is seeking a Data Scientist to support data pipeline development, validation, and analysis within a cloud-based Health IT data platform. This role is hands-on and delivery-focused, with an emphasis on building reliable, reproducible data workflows using SQL, Python, and PySpark in an Azure Synapse environment.


A core expectation of this role is the ability to work across the full data lifecycle, from ingestion through transformation to final dataset delivery, while maintaining data quality and traceability. The ideal candidate is comfortable debugging data issues end-to-end, understands how data structure and join logic impact outputs, and applies disciplined validation and documentation practices. This role also supports exploratory data analysis and the development of derived datasets to enable analytics and downstream use cases. The position will work extensively with healthcare data originating from EHR systems and interface feeds, including HL7 v2 and FHIR data, clinical terminology, and source-to-target data mappings.


Key Responsibilities

  • Data Pipeline Development: Develop, maintain, and optimize data pipelines using SQL, Python (pandas), and PySpark.

  • Advanced Technology Applications: Execute and manage notebook-based workflows within Azure Synapse, including debugging and documentation.

  • Data Formats: Process and transform structured and semi-structured data in formats such as CSV, JSON/NDJSON, and Parquet.

  • ETL/ELT Pipelines: Work within ETL/ELT pipelines across raw, curated, and production data layers.

  • Data Ingestion: Ingest, profile, map, and transform healthcare data from EHR systems and interface feeds while preserving source lineage and clinical context.


ATA, LLC | 752 Walker Road | Suite D | Great Falls, VA 22066 | www.ata-llc.com


Data Quality and Validation

  • Perform structured data validation, including row counts, null checks, duplicate detection, schema validation, and allowed value enforcement.

  • Identify and resolve data quality issues such as schema drift, inconsistencies, and transformation errors across pipeline stages.

  • Apply repeatable testing and validation practices, including reproducing issues, verifying fixes, and ensuring data reliability prior to downstream use.

  • Validate source-to-target mappings and reconcile records across source and destination systems during data conversion and migration activities.


Data Analysis and Dataset Development

  • Conduct exploratory data analysis to identify patterns, anomalies, and data quality concerns.

  • Develop derived datasets to support reporting, analytics, and downstream data use cases.

  • Collaborate with stakeholders to translate data requirements into usable datasets and metrics.


Data Modeling and Structure Awareness

  • Interpret and work with data schemas, including column definitions, data types, primary and composite keys, and table relationships.

  • Manage dataset grain and understand how join strategies (e.g., one-to-one vs. one-to-many) impact row counts and outputs.


Debugging and Troubleshooting

  • Trace data issues from source ingestion through transformation logic to final outputs.

  • Use logs and debugging approaches to diagnose and resolve pipeline issues.

  • Document data transformations, assumptions, mappings, and validation results in a clear and consistent manner.

  • Collaborate with engineers, analysts, and stakeholders to ensure data usability, integrity, and alignment with requirements.


ATA, LLC | 752 Walker Road | Suite D | Great Falls, VA 22066 | www.ata-llc.com


Advanced Technology Applications

  • Communicate data issues, findings, and workflow updates with technical team members.


Minimum Qualifications

  • Hands-on experience writing SQL queries for data transformation and analysis.

  • Experience using Python (e.g., pandas) for data processing.

  • Hands-on experience using PySpark for distributed data processing.

  • Experience working within cloud-based data platforms, preferably Azure Synapse or similar.

  • Understanding ETL/ELT concepts and data pipeline architecture.

  • Experience working with structured and semi-structured data formats (CSV, JSON, Parquet).

  • Familiarity with Git and collaborative development workflows.

  • Strong problem-solving and debugging skills across data pipelines.

  • Ability to validate and ensure data quality through structured checks and testing practices.

  • Strong written and verbal communication skills.


Preferred Qualifications

  • Experience working with healthcare interoperability standards and message formats, particularly HL7 v2 and FHIR.

  • Familiarity with clinical terminology and code systems such as SNOMED CT, ICD-10, LOINC, RxNorm, or CPT.

  • Experience supporting large-scale EHR data conversion or migration efforts, particularly between RPMS and Oracle Health/Cernerโ€”or a comparable legacy-to-modern EHR migration.

  • Understanding of clinical data mapping, terminology normalization, provenance, and validation across source and target systems


General personal traits we know will connect well with the team

  • Dependable, self-directed, and able to meet commitments.

  • Comfortable learning new subject areas and solving unfamiliar problems.

  • Enjoys collaborating across technical and subject-matter disciplines.

  • Pragmatic and able to select the appropriate tool for the requirement.


ATA, LLC | 752 Walker Road | Suite D | Great Falls, VA 22066 |


Advanced Technology Applications



  • About ATA: A leading provider of full-stack data and AI solutions with deep mission experience supporting the Department of Defense, Department of Homeland Security, IC, and federal agencies. Founded in 2008 and headquartered in Virginia, ATA specializes in secure, scalable, and operationally ready technologies that transform data into actionable insight. With a proven track record in advanced analytics, software development, and technology integration, ATA is uniquely positioned to accelerate federal organizations in a number of ways by leveraging powerful contracting options and delivering cutting-edge, automation-enhanced, AI-assisted capabilitiesโ€”tailored to need and mission assurance imperatives. We believe our diversity of infrastructure, data, and application experience is valuable and is one of the attributes that sets ATA apart.


Summary of Benefits: We expect each member of our team to fully engage creatively and work collaboratively and perform each day to the best of their ability.To support this, we have created a benefit package focused on professional growth, achieving a healthy work-life balance, and participation in the long-term success of the company.Our benefits include generous paid time-off; an employee incentive program; continuous learning culture, Internal


Investment Projects (IIP), virtual brown-bags/level-ups, and other professional development activities; recruiting bonuses; 3% 401k Safe Harbor contributions; Medical/Dental/Vision, Long & Short-term Disability, AD&D insurance, and Life Insurance.


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Cherokee Federal logo

About Cherokee Federal

Sourced by ZipRecruiter

Cherokee Federal - a division of Cherokee Nation Businesses - is a team of tribally owned federal contracting companies focused on building solutions, solving complex challenges, and serving the nation's mission around the globe for more than 60 federal clients. Our team of companies manages nearly 1,000 projects of all sizes across the construction, consulting, engineering and manufacturing, health, and technology portfolios. Since 2012, the Cherokee Federal team of companies has won more than $5 billion in government contracts. Our 3,000+ employees work in 26 countries, 50 states and 2 U.S. territories. Why choose Cherokee Federal? Visit our website and learn about the great reasons to join our team. cherokee-federal.com

Industry

Architectural services

Company size

1,001 - 5,000 Employees

Headquarters location

Tulsa, OK, US

Year founded

1969

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