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Biomedical Data Visualization Jobs (NOW HIRING)

Lexical Intelligence

NLM Data Scientist

Bethesda, MD · On-site

... biomedical information sources. Our Natural Language Processing (NLP) and analytics software is ... Proficiency with data visualization tools such as Tableau, Splunk, Google Analytics * Experience ...

Lexical Intelligence LLC

NLM Data Scientist

Bethesda, MD · On-site

$100K - $115K/yr

... biomedical information sources. Our Natural Language Processing (NLP) and analytics software is ... Proficiency with data visualization tools such as Tableau, Splunk, Google Analytics * Experience ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

Tableau, Power BI, R Shiny, or similar dashboard/data visualization experience. * Experience with ... Experience with federal, public sector, law enforcement, financial, healthcare, biomedical, or ...

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Biomedical Data Visualization information

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$54K

$109.5K

$161.5K

How much do biomedical data visualization jobs pay per year?

As of Sep 12, 2026, the average yearly pay for biomedical data visualization in the United States is $109,451.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $123,000.00 per year, depending on experience, location, and employer.

What is biomedical data visualization?

Biomedical data visualization is the process of creating graphical representations of complex biological and medical data to help researchers and healthcare professionals understand patterns, trends, and insights within the data. This field combines principles from biology, data science, and computer graphics to translate large datasets—such as patient records, genomic information, or clinical trial results—into interactive charts, graphs, and visual tools. Effective biomedical data visualization can improve decision-making, enhance communication among teams, and support scientific discoveries by making data more accessible and interpretable.

What are the key skills and qualifications needed to thrive as a biomedical data visualization specialist?

To thrive as a Biomedical Data Visualization Specialist, you need a strong background in data analysis, statistics, and biomedical sciences, often supported by a relevant degree. Proficiency with visualization tools such as Tableau, R, Python (matplotlib, seaborn), and familiarity with biomedical databases are typically required. Strong attention to detail, creativity, and the ability to communicate complex information clearly are essential soft skills. These competencies ensure accurate, insightful visualizations that help researchers and clinicians make informed decisions based on complex biomedical data.

What are some common challenges faced when visualizing biomedical data, and how can they be addressed in this role?

One common challenge in biomedical data visualization is handling large and complex datasets that often come from diverse sources, such as clinical trials, genomics, or imaging. Ensuring data integrity, managing missing values, and selecting appropriate visualization techniques are crucial for clear and accurate insights. Professionals in this role frequently collaborate with researchers and clinicians to understand data context and tailor visualizations to specific audiences. Staying current with visualization tools and best practices helps address these challenges and ensures the effective communication of critical biomedical information.

What is the difference between Biomedical Data Visualization vs Biomedical Data Analyst?

AspectBiomedical Data VisualizationBiomedical Data Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Data Science, or related fields; proficiency in visualization toolsBachelor's or Master's in Bioinformatics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch labs, healthcare institutions, biotech companies focusing on visual data representationResearch institutions, healthcare, biotech firms analyzing and interpreting data
Employer & Industry UsageUsed to create visual representations of biomedical data for research and presentationUsed to analyze, interpret, and report biomedical data for decision-making

Biomedical Data Visualization focuses on creating visual representations of biomedical data to aid understanding and communication. In contrast, Biomedical Data Analysts interpret and analyze data to derive insights. Both roles often require similar educational backgrounds but serve different functions within the data lifecycle.

What other helpful pages are available for Biomedical Data Visualization?

Other pages related to Biomedical Data Visualization:

Infographic showing various Biomedical Data Visualization job openings in the United States as of September 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 100% In-person job distribution, with an average salary of $109,451 per year, or $52.6 per hour.

Data Scientist ::Onsite in NYC, NY (Onsite)

New York, NY • On-site

Talent Movers
See more jobs at Talent Moversexternal

Contractor

Re-posted 17 days ago

Job description

Title : Data Scientist

Location: Onsite in NYC, NY (Onsite)

Rate: ON C2C/W2

 

Top 3 must-have HARD skills:

Experience with hardware sensors and real-world data analysis
Direct experience working with biosensors or similar hardware, and analyzing the resulting data.
Signal processing expertise
Ability to process time domain signals and/or medical imaging systems, which is crucial for biosensor data.
Advanced programming and data manipulation
3+ years of hands-on experience with Python, R, MATLAB, or SQL for data extraction, manipulation, and visualization, including proficiency with scientific computing and analysis packages (NumPy, SciPy, Pandas, Scikit-learn, etc.).

Good to have skills:

Experience presenting findings from statistical and machine learning methods to diverse audiences.
Proficiency in data structures and algorithms.
Experience with data visualization libraries (Matplotlib, Pyplot, seaborn, ggplot2).
Experience working with large datasets.
Familiarity with scientific computing and analysis packages (dplyr, caret).
Advanced degree (Master’s or PhD) in computer science, statistics, neuroscience, biomedical engineering, or related field.

Job Description:

Summary:
The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. The Data Scientist will contribute to biosensor data analysis and help to guide future biosensing R&D.
Job Responsibilities:
Execute, debug, and optimize distributed compute workflows for metric computation, analysis, and modeling across large datasets.
Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, and make valuable discoveries leading to prototype biosensor development and product improvement.
Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the biosensor data.
Generate and test hypotheses and analyze and interpret the results of product experiments.
Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation.
Leverage data visualization to help the team make decisions about future R&D directions to go.
Skills:
Experience with hardware sensors, and data analysis pertaining to real-world data.
Experience with signal processing pertaining to time domain signals and/or medical imaging systems
Experience presenting findings from statistical and machine learning methods to diverse audiences
Experience working with large datasets.
3+ years of experience performing data extraction, manipulation, and visualization using programming languages (e.g., Python), scientific computing languages (e.g., R, MATLAB), or SQL.
Proficiency in data structures and algorithms.
Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, caret.
Experience with data visualization libraries such as Matplotlib, Pyplot, seaborn, ggplot2.
Education/Experience:
Master of Science or PhD degree in computer science, statistics, neuroscience, biomedical engineering, or other relevant field.