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Remote Health Data Analyst Jobs (NOW HIRING)

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

ERG

Occupational Safety and Health Data Analyst

... a remote environment to accomplish assignments in a timely manner • Experience or strong interest in data analysis, public health, occupational safety, epidemiology, or related fields • ...

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Remote Health Data Analyst information

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$34K

$82.6K

$136K

How much do remote health data analyst jobs pay per year?

As of Jun 6, 2026, the average yearly pay for remote health data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What Does a Remote Health Data Analyst Do?

The job duties of a remote health data analyst include performing analysis on datasets related to the healthcare industry. In this career, you may work from home to gather relevant data from different sources, such as medical records, operational logs, and billing databases. The responsibilities of a health data analyst include using data to define healthcare trends, seek out areas for cost reduction, and analyze the cost and effectiveness of treatments. As a telecommute worker, you send reports to healthcare management personnel electronically, and you may have to communicate with them to answer questions after report submission.

What is a Remote Health Data Analyst?

A Remote Health Data Analyst is a professional who works primarily from a remote location to collect, process, and analyze healthcare data. They use statistical tools and software to interpret data from medical records, insurance claims, patient surveys, and other health information sources. Their insights help healthcare organizations improve patient care, optimize operations, and ensure regulatory compliance. Remote Health Data Analysts often collaborate with medical staff, IT teams, and administrators using digital communication tools. This role requires strong analytical skills, attention to detail, and proficiency in data management systems.

How does a Remote Health Data Analyst typically collaborate with healthcare teams while working offsite?

Remote Health Data Analysts frequently collaborate with clinicians, IT professionals, and data scientists through digital communication tools such as video conferencing, secure messaging, and shared data platforms. Regular virtual meetings are common to discuss project progress, clarify data requirements, and ensure alignment on healthcare outcomes. While working remotely offers flexibility, it also requires proactive communication and strong organizational skills to manage multiple projects and maintain data security standards. Building trust and maintaining clear documentation are essential for effective remote teamwork in this role.

What are the key skills and qualifications needed to thrive as a Remote Health Data Analyst, and why are they important?

To thrive as a Remote Health Data Analyst, you need strong analytical skills, knowledge of healthcare data standards, and at least a bachelor's degree in health informatics, statistics, or a related field. Proficiency with data analysis tools such as SQL, Python, R, and experience with electronic health record (EHR) systems and data visualization platforms like Tableau or Power BI are typically required. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for interpreting data and collaborating remotely with teams. These skills ensure accurate data insights, enable informed decision-making, and support the delivery of efficient healthcare services from a remote environment.
More about Remote Health Data Analyst jobs
What cities are hiring for Remote Health Data Analyst jobs? Cities with the most Remote Health Data Analyst job openings:
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Remote Health Data Analyst jobs near you
Infographic showing various Remote Health Data Analyst job openings in the United States as of May 2026, with employment types broken down into 14% Full Time, and 86% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Health Data Analyst - AI Trainer

Health Data Analyst - AI Trainer

DataAnnotation

Washington, DC • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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