Clinical Data Analyst

A Clinical Data Analyst analyzes and interprets clinical data to support evidence-based decision-making in healthcare, improving patient outcomes and optimizing healthcare delivery.
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Clinical Data Analyst

National (USA)
Base Salary
$72,495 / year
Additional Benefits
Bachelor's Degree

The average salary for Clinical Data Analyst is $72,495 / year according to

There are no updated reports for Clinical Data Analyst salaries. You can check potential lateral job opportunities in this information stack to find related salary information.

Clinical Data Analyst role may have an alternate title depending on the company. To find more information, you can check

Career Information

As a Clinical Data Analyst, you will be responsible for analyzing and interpreting clinical data to support medical research and decision-making. You will need strong data analysis skills and experience with clinical databases and statistical analysis. Strong analytical and problem-solving skills are essential, as you will be responsible for providing insights and recommendations based on clinical data.

The average salary for Clinical Data Analyst is $72,495 / year according to
AI Disclaimer
The following text about the Job role of Clinical Data Analyst has been generated by an AI model developed by OpenAI. While efforts have been made to ensure the accuracy and coherence of the content, there is a possibility that the model may produce hallucinated or incorrect information. Therefore, we strongly recommend independently verifying any information provided in this text before making any decisions or taking any actions based on it.

A Clinical Data Analyst is a professional who plays a vital role in the healthcare industry by analyzing and interpreting clinical data to improve patient care and outcomes. They work with large datasets, extracting valuable insights that inform decision-making and drive evidence-based practices.

One of the most important skills for a Clinical Data Analyst is proficiency in data analysis and statistical methods. They must be able to clean, organize, and analyze complex healthcare datasets using statistical software and programming languages. This allows them to identify patterns, trends, and correlations in the data, which can be used to inform clinical research and improve patient care.

Another essential skill for a Clinical Data Analyst is a strong understanding of healthcare systems and terminology. They must be familiar with medical coding systems, such as ICD-10 and CPT, and have knowledge of clinical workflows and procedures. This enables them to accurately interpret and analyze clinical data within the context of healthcare practices.

In addition to technical skills, a Clinical Data Analyst must possess strong critical thinking abilities. They must be able to evaluate the quality and reliability of data, identify potential biases or errors, and draw valid conclusions. They must also be able to communicate their findings effectively to healthcare professionals and stakeholders.

Furthermore, a Clinical Data Analyst must have excellent attention to detail. They must be meticulous in their data analysis, ensuring accuracy and precision in their work. They must also be able to identify outliers or anomalies in the data that may require further investigation.

Moreover, a Clinical Data Analyst must stay up-to-date with the latest advancements in healthcare technology and data analytics. They must continuously learn and adapt to new tools, methodologies, and regulations in order to effectively analyze and interpret clinical data.

An important task for a Clinical Data Analyst is to collaborate with healthcare professionals and researchers. They must work closely with clinicians, nurses, and other healthcare staff to understand their data needs and provide meaningful insights. They may also collaborate with researchers to design and conduct clinical studies and trials.

Additionally, a Clinical Data Analyst may be involved in developing and implementing data management and governance strategies. They may work with IT departments and data privacy officers to ensure the security and confidentiality of patient data, while also complying with relevant regulations, such as HIPAA.

Overall, a Clinical Data Analyst plays a crucial role in improving patient care and outcomes through data analysis and interpretation. Their skills in data analysis, healthcare systems, critical thinking, attention to detail, and collaboration are essential for extracting valuable insights from clinical data and driving evidence-based practices. By fulfilling their role effectively, Clinical Data Analysts contribute to the advancement of healthcare and the well-being of patients.

Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.

High-ROI Programs

Most roles require at least a bachelor's degree. To remain competitive, job seekers should consider specialization or skill-specific programs such as specialization, bootcamps or certifications.
Certification Programs
Consider pursuing specialized certifications or vendor-specific programs to enhance your qualifications and stand out in the job market.

Microsoft Certified: Azure Data Scientist Associate


The Microsoft Certified: Azure Data Scientist Associate is a high-ROI program designed for professionals who have expertise in applying data science and machine learning techniques to implement and manage machine learning workloads on Azure.

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AWS Certified Machine Learning — Specialty Certification


The AWS Certified Machine Learning - Specialty certification covers a wide range of topics, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations on the AWS Cloud. 

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AWS Certified Data Analytics — Specialty


The AWS Data Analytics Certification program validates a deep understanding of AWS data analytics services and their integration with each other to derive insights from data, making it suitable for individuals pursuing a role focused on data analytics.

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Microsoft Certified: Azure Enterprise Data Analyst Associate


The Azure Data Analyst Certification is a high-ROI program designed for professionals who have expertise in designing, creating, and deploying enterprise-scale data analytics solutions.

View More

Google Certified Professional Machine Learning Engineer

The Google Machine Learning Certification is a high-ROI program designed for ML engineers who want to gain specialized machine learning skills using Google Cloud technologies.

View More

Databricks Certified Data Engineer Associate

The Databricks Data Engineer Certification program is highly sought after, designed to evaluate an individual's proficiency in utilizing the Databricks Lakehouse Platform for performing fundamental data engineering tasks.

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Specialty Courses improving
If you want to improve your skills and knowledge in a particular field, you should think about enrolling in a Nanodegree or specialization program. This can greatly improve your chances of finding a job and make you more competitive in the job market.

Mathematics for Machine Learning and Data Science Specialization


Introduction to Data Science


IBM Data Analyst Professional Certificate


Learn Intermediate Python


Data Science with Databricks for Data Analysts Specialization


How to Become a Business Analyst


Complete linear algebra: theory and implementation in code


This course teaches concepts in linear algebra and matrix analysis, and demonstrates their implementation in MATLAB and Python.

Resource Stacks

We are soon crowdsourcing these resource stacks to collate the best resources, such as publications, community groups, job boards, etc., that are practically suitable for every contextual stack.
Discover the wide array of publications that professionals in this role actively engage with, expanding their knowledge and staying informed about the latest industry trends and developments.
Communities updating
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
Research updating
We are currently in the process of updating contextual resources and we will be adding the new ones to the list shortly.
AI Disclosure: We are testing AI technologies to ensure the accuracy and coherence of recommendations. However, it is important to note that there is a possibility that the model may create hallucinated or incorrect inferences. Therefore, we highly recommend independently verifying any information provided in these stacks before making any decisions or taking any actions based on it.

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