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Biomedical Data Visualization Jobs (NOW HIRING)

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

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

Medical University of South Carolina

$70K - $88K/yr

Bachelor's degree in computer science, data science, biomedical informatics, biostatistics ... Experience with data visualization, predictive modeling, and clinical research analytics.

Zifo

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... We look for Science - Biotechnology, Pharmaceutical Technology, Biomedical Engineering ...

Zifo

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... We look for Science - Biotechnology, Pharmaceutical Technology, Biomedical Engineering ...

Zifo

Sr. Data Engineer

Raleigh, NC

$111K - $133K/yr

Develop data visualization tools to communicate insights, * Provide consulting inputs for ... We look for Science - Biotechnology, Pharmaceutical Technology, Biomedical Engineering ...

Exatech Inc

Azure Data Solutions Architect

Dallas, TX · On-site

$62.75 - $81.75/hr

Background in biomedical data processing is a plus. * Experience in GenAI and Agentic AI. * Subject ... Experience in applying data curation, virtualization, workflow, and advanced visualization ...

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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.

Junior Data Scientist

Arlington, VA • On-site

AITHERAS, LLC
IT Services • 11 - 50 employees
Learn more about AITHERAS, LLCexternal

$100K - $120K/yr

Full-time

Re-posted 22 days ago

Job description

Junior Data Scientist / Performance Data Analyst I

Location: Washington, DC / Hybrid / Government Facility as Required
Clearance / Background: U.S. Citizen required; ability to obtain DOJ Public Trust and Secret clearance; active Secret preferred
Experience Level: 1–3 years

Role Summary

The Junior Data Scientist / Performance Data Analyst I supports a federal Management Information System program by helping collect, clean, validate, analyze, and visualize operational and performance data.

This role is ideal for an early-career data scientist with strong Python, R, SQL, Tableau, machine learning, NLP, and statistical analysis skills who is ready to progress from research, healthcare, or academic data work into federal mission analytics.

Key Responsibilities

  • Collect, clean, validate, and analyze structured and semi-structured program data.

  • Build SQL, Python, and R scripts to extract data, run calculations, automate recurring analysis, and reduce manual reporting effort.

  • Develop and maintain Tableau dashboards, visual reports, charts, and performance summaries.

  • Support data quality reviews by identifying anomalies, missing values, inconsistent records, and reporting defects.

  • Assist senior analysts with statistical modeling, machine learning, trend analysis, and performance measurement.

  • Translate complex datasets into clear summaries for non-technical stakeholders.

  • Document data sources, business rules, transformation logic, assumptions, and analytical methods.

  • Support recurring weekly, monthly, quarterly, and ad hoc reporting requirements.

  • Review model outputs and error patterns to recommend improvements to analytical workflows.

  • Collaborate with senior data scientists, program analysts, project managers, and government stakeholders.

Required Qualifications

  • Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Information Systems, Neuroscience, Public Health Analytics, or a related quantitative field.

  • 1–3 years of data science, data analytics, research analytics, BI, or machine learning project experience.

  • Hands-on Python experience using pandas, NumPy, scikit-learn, matplotlib, spaCy, Keras, or similar libraries.

  • R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages.

  • SQL experience for querying, joining, filtering, and preparing datasets.

  • Tableau, Power BI, R Shiny, or similar dashboard/data visualization experience.

  • Experience with machine learning classification, NLP, model evaluation, or predictive analytics.

  • Ability to inspect model errors, validate outputs, and communicate improvement opportunities.

  • Strong Excel and Microsoft Office skills.

  • Ability to explain technical findings to non-technical stakeholders.

  • U.S. citizenship and ability to obtain required federal suitability/clearance.

Preferred Qualifications

  • Active Secret clearance or prior federal suitability.

  • Experience with federal, public sector, law enforcement, financial, healthcare, biomedical, or large statistical datasets.

  • Experience supporting performance metrics, KPI reporting, operational reporting, or program evaluation.

  • Experience building client-facing dashboards or interactive data applications.

  • Experience with BERT, NLP, unstructured text, topic segmentation, or terminology data.

  • Familiarity with data governance, data privacy, PII handling, CUI, or secure data environments.

  • AWS, Git, Jupyter Notebook, or cloud analytics exposure.

Tools / Technologies

Python, R, SQL, Tableau, Excel, Jupyter Notebook, Git, AWS, pandas, NumPy, scikit-learn, spaCy, Keras, tidyverse, tidymodels, ggplot2, Shiny, NLP, BERT, dashboards, data visualization, statistical modeling.

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