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Healthcare Data Science Jobs in Minnesota (NOW HIRING)

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Healthcare Data Science information

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$45.1K

$161.6K

$238.5K

How much do healthcare data science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for healthcare data science in Minnesota is $161,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,800.00 and $166,500.00 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.

What are the most commonly searched types of Healthcare Data Science jobs in Minnesota?

The most popular types of Healthcare Data Science jobs in Minnesota are:

What are popular job titles related to Healthcare Data Science jobs in Minnesota?

For Healthcare Data Science jobs in Minnesota, the most frequently searched job titles are:

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

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

What cities in Minnesota are hiring for Healthcare Data Science jobs?

Cities in Minnesota with the most Healthcare Data Science job openings:

Healthcare Data Science jobs near you
Infographic showing various Healthcare Data Science job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 9% Part Time, and 6% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $161,621 per year, or $77.7 per hour.

Senior Healthcare Data Modeler

Techvilla Solutions

Wayzata, MN

Full-time

Posted 4 days ago

Job description

Primary Responsibilities
  • Design and implement enterprise data models and data architecture for large, complex healthcare systems.
  • Translate business and technical requirements into scalable data models and end-to-end data solutions.
  • Develop data strategies, roadmaps, and data management solutions supporting analytics and enterprise reporting.
  • Design normalized OLTP, OLAP, MDM, and dimensional models, including Star schemas, SCDs, role-playing dimensions, hierarchies, and data classification.
  • Develop and review complex SQL queries, stored procedures, DDL, DML, and DCL using ANSI standards.
  • Optimize SQL queries and analyze database performance.
  • Define and implement data quality, profiling, governance, security, metadata management, MDM, archival, and migration strategies.
  • Ensure compliance with healthcare data security and privacy requirements, including HIPAA, PHI, and PII.
  • Collaborate with Data Managers, Data Integration Leads, Data Engineers, and business stakeholders.
  • Provide technical leadership, problem-solving, presentations, and recommendations for complex data initiatives.
Required Skills & Qualifications
  • 8+ years of experience in Data Modeling, Data Architecture, or Data Management.
  • 5+ years of hands-on experience with Erwin Data Modeler.
  • 5+ years of experience working with healthcare data and healthcare information systems.
  • Strong experience with Medicaid, Medicare, and Commercial healthcare datasets; Medicaid experience is highly preferred.
  • 7+ years of advanced SQL experience, including complex queries, stored procedures, DDL, DML, DCL, and query optimization.
  • Strong expertise in OLTP, OLAP, MDM, and dimensional data modeling.
  • Experience with Star schemas, Slowly Changing Dimensions (SCD), role-playing dimensions, dimensional hierarchies, and data classification.
  • Strong knowledge of Data Governance, Data Quality, Data Profiling, Data Security, Metadata Management, MDM, Data Archival, and Data Migration.
  • Strong understanding of HIPAA, PHI, PII, and healthcare data privacy/security requirements.
  • Excellent problem-solving, communication, influencing, presentation, and stakeholder management skills.
  • Ability to work independently and take ownership of complex data initiatives.
Preferred Skills
  • Experience with Microsoft Azure data services, including Azure Data Lake Storage, Azure Data Factory, Microsoft Purview, and Azure Maps.
  • Experience with Snowflake.
  • Experience with Power BI or Tableau.
  • Experience designing and implementing large-scale healthcare data warehouse and analytics solutions.

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