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Healthcare Data Science Jobs (NOW HIRING)

Healthcare Data Scientist

San Francisco, CA ยท On-site

$120 - $180/hr

Train and evaluate models using real-world healthcare datasets. Healthcare Data Science & Analytics * Analyze complex healthcare datasets from multiple clinical sources. * Identify trends, patterns ...

We are seeking a Healthcare Data Scientist (Real-World Evidence) to answer complex healthcare and biopharma questions using large-scale real-world data and help shape the next generation of AI ...

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 ...

Stay current on the latest advancements in healthcare data science and machine learning. Qualifications: Minimum 5 years of experience in data science or a related field. Less ok too, if they have a ...

Healthcare Data Analyst

Bannockburn, IL ยท On-site

$70K - $117K/yr

... healthcare cost data. * Translates specific business issues and questions into appropriate ... Bachelor's Degree in relevant field (Information Science, Computer Science, Actuarial Science ...

Data Science Fellow

Chicago, IL ยท On-site

$51K - $87K/yr

You will be responsible for data science projects across the healthcare domains of clinical & operations, supply chain, pharmacy, and healthcare strategy.You will work with executive mentor(s) and ...

5+ SAS & SQL programming, 3+ years data science in healthcare SAS EG, SAS Studio, SQL Developer, Office 365 Microsoft Visio, Tableau, Power BI, JIRA, Epic Systems including Clarity database, Healt ...

Senior Data Scientist

Palo Alto, CA ยท On-site

$160K - $190K/yr

Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI, and cybersecurity. We look for people who are smart, open, and enjoyable to work with. We invest in ...

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Healthcare Data Science information

See salary details

$46K

$165K

$243.5K

How much do healthcare data science jobs pay per year?

As of Aug 11, 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 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 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.

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 can you do with a degree in healthcare data science?

A degree in healthcare data science prepares individuals to analyze medical data, develop predictive models, and improve patient outcomes. Graduates can work as data analysts, data scientists, or informaticists in hospitals, healthcare companies, or research institutions, often using tools like Python, R, and SQL. The role involves interpreting complex data to support clinical decisions and healthcare policies.

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.

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.
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:
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, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Healthcare Data Scientist

Medclinicx

San Francisco, CA โ€ข On-site

$120 - $180/hr

Other

Posted 5 days ago


Job description

Med Clinic X is a healthcare technology company focused on building advanced AI-driven digital health systems for healthcare organizations across the United States.

We design and develop healthcare SaaS platforms, patient portals, AI-powered clinical systems, telemedicine solutions, automation tools, and data-driven healthcare products for clinics, hospitals, and healthcare providers.

Our mission is to transform healthcare using data, machine learning, and intelligent systems that improve patient outcomes and operational efficiency.

Job Overview

We are seeking a Healthcare Data Scientist to design and build advanced analytics models, machine learning systems, and AI-driven healthcare solutions.

In this role, you will work with large-scale healthcare datasets from clinical systems, EHR platforms, and SaaS applications to build predictive models and intelligent systems that support healthcare decision-making.

You will collaborate with engineers, product teams, clinical stakeholders, and data analysts to develop AI solutions that power the next generation of digital healthcare products.

Key Responsibilities
  • Build predictive models for healthcare outcomes and clinical insights.
  • Develop machine learning algorithms using structured and unstructured healthcare data.
  • Design AI systems for patient risk prediction and operational optimization.
  • Train and evaluate models using real-world healthcare datasets.
Healthcare Data Science & Analytics
  • Analyze complex healthcare datasets from multiple clinical sources.
  • Identify trends, patterns, and correlations in clinical and operational data.
  • Develop statistical models to support healthcare decision-making.
  • Perform feature engineering for healthcare AI systems.
  • Support AI features for healthcare SaaS platforms and patient portals.
  • Improve personalization and automation in healthcare applications.
  • Analyze user behavior and system performance in digital health platforms.
  • Build data-driven insights for healthcare product teams.
  • Work with engineers to deploy machine learning models into production systems.
  • Collaborate with product managers to define AI-driven healthcare features.
  • Support integration of AI models with healthcare APIs and platforms.
  • Ensure scalability and reliability of healthcare AI systems.
Healthcare Technology Areas You Will Work With

Train and evaluate models for disease diagnosis, clinical risk mapping, and workflow assistant tools.

Predictive analytics systems

Build models to estimate readmission risks, hospital length of stay, and operational bottlenecks.

Support clinical decision-making by surfacing patient flags directly in doctor queues.

Engineer features from longitudinal patient charts to map cardiac, diabetic, and respiratory risk trajectories.

Clinical NLP engines

Leverage LLMs and clinical BERT to extract medical terms, intents, and symptoms from doctor notes.

Healthcare SaaS intelligence

Deploy SaaS intelligence layers optimizing doctor schedules and automating intake briefs.

Core Technical Requirements

Statistical & Predictive Modeling Required

Deep Learning (TensorFlow/PyTorch) Highly Valued

EHR/EMR Dataset architectures Highly Valued

HIPAA Compliance & MLOps Preferred

Required Qualifications
  • Bachelorโ€™s or Masterโ€™s in Data Science, CS, Stats, ML, or related field.
  • Strong experience in statistical modeling and predictive machine learning.
  • Proficiency in Python and standard ML libraries (Pandas, Scikit-learn).
  • Experience with SQL and relational/non-relational database query optimization.
Preferred Qualifications
  • Experience in US healthcare or healthcare SaaS platforms.
  • Knowledge of HIPAA regulations, anonymization, and data privacy.
  • Experience working with large EMR/EHR datasets or clinical notes.
  • Knowledge of HL7, FHIR, or healthcare data standards.
Why Join Med Clinic X?
  • Build ML systems directly used to improve real-world US clinical delivery.
  • Analyze large-scale, high-complexity longitudinal patient datasets.
  • Collaborate with top-tier engineers and clinical decision makers.
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