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Senior Biomedical Data Scientist Jobs (NOW HIRING)

Axle

Data Scientist II

Rockville, MD

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

Axle

Data Scientist II

Rockville, MD · On-site

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

Axle

Data Scientist II

Rockville, MD

... and data science applications to research centers and healthcare organizations nationally and ... With experts in biomedical science, software engineering, and program management, we focus on ...

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All JobsBiomedical Data Scientist JobsSenior Biomedical Data Scientist Jobs

Senior Biomedical Data Scientist information

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$41.5K

$142.5K

$201K

How much do senior biomedical data scientist jobs pay per year?

As of Jul 27, 2026, the average yearly pay for senior biomedical data scientist in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What is the highest paid job in biomedical science?

In biomedical science, senior roles such as biomedical directors, principal scientists, or chief scientific officers tend to be the highest paid, often earning six-figure salaries. These positions typically require advanced degrees, extensive experience, and leadership skills, and may involve overseeing research teams or strategic planning in biotech or pharmaceutical companies.

What are Senior Biomedical Data Scientists?

Senior Biomedical Data Scientists are experienced professionals who analyze and interpret complex biomedical data to advance research, healthcare, and medical innovation. They use statistical methods, machine learning, and computational tools to extract insights from large datasets such as genomic sequences, electronic health records, and clinical trial results. In addition to technical skills, they often lead projects, collaborate with interdisciplinary teams, and help translate data findings into actionable solutions for improving patient outcomes and advancing scientific knowledge.

How does a Senior Biomedical Data Scientist typically collaborate with clinical teams and researchers on interdisciplinary projects?

A Senior Biomedical Data Scientist often works closely with clinicians, biostatisticians, and researchers to translate complex biomedical problems into data-driven solutions. This collaboration usually involves participating in regular project meetings, understanding clinical objectives, and helping to design experiments or studies. The role also requires clear communication to interpret and present data findings to non-technical stakeholders, ensuring that analyses support clinical or research goals. Effective teamwork and adaptability are key, as projects frequently evolve based on new data or research directions.

What is the difference between Senior Biomedical Data Scientist vs Biomedical Data Scientist?

AspectSenior Biomedical Data ScientistBiomedical Data Scientist
Required CredentialsMaster's or PhD in Bioinformatics, Data Science, or related fields; experience with programming and statistical toolsBachelor's or Master's in relevant fields; foundational knowledge in data analysis and biology
Work EnvironmentResearch labs, healthcare companies, biotech firms; often involved in complex data projectsAcademic institutions, healthcare organizations, biotech companies; focused on data collection and analysis
Employer & Industry UsageUsed in biotech, pharma, healthcare research; roles often involve leadership in projectsCommon in research, clinical, and academic settings; entry to mid-level roles

The main difference between a Senior Biomedical Data Scientist and a Biomedical Data Scientist lies in experience, responsibilities, and expertise. Senior roles typically require advanced degrees and extensive experience, involving leadership and complex project management, whereas Biomedical Data Scientists are often entry to mid-level professionals focused on data analysis and research support.

What is the 80 20 rule in data science?

The 80/20 rule, also known as Pareto principle, suggests that roughly 80% of effects come from 20% of causes. In data science, it often means that a small subset of features or data points contribute most to model performance or insights, guiding focus on the most impactful variables during analysis and feature selection.

What does a senior biomedical scientist earn?

A senior biomedical data scientist typically earns between $90,000 and $130,000 annually, depending on experience, location, and industry sector. They often have advanced skills in data analysis, programming, and knowledge of biomedical research tools, which can influence salary levels.

Is 40 too late for data science?

Age is not a barrier to becoming a Senior Biomedical Data Scientist, as the field values skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and domain expertise, often through certifications or advanced degrees. Success depends on your ability to adapt and build a strong portfolio of projects and skills regardless of age.

What are the key skills and qualifications needed to thrive as a Senior Biomedical Data Scientist, and why are they important?

To thrive as a Senior Biomedical Data Scientist, you need advanced expertise in data analysis, machine learning, and statistical modeling, typically backed by a graduate degree in bioinformatics, computer science, or a related field. Proficiency with programming languages like Python or R, experience with big data platforms, and familiarity with scientific computing tools are essential, along with certifications in data science or biomedical informatics being advantageous. Strong problem-solving abilities, communication skills, and the capacity to collaborate with interdisciplinary teams set top performers apart. These competencies are critical for translating complex biomedical data into actionable insights that drive research, clinical outcomes, and innovation.
What cities are hiring for Senior Biomedical Data Scientist jobs? Cities with the most Senior Biomedical Data Scientist job openings:
What are the most commonly searched types of Biomedical Data Scientist jobs? The most popular types of Biomedical Data Scientist jobs are:
What states have the most Senior Biomedical Data Scientist jobs? States with the most job openings for Senior Biomedical Data Scientist jobs include:
Senior Biomedical Data Scientist jobs near you
Research Associate Data Scientist

Research Associate Data Scientist

Cedars Sinai

Los Angeles, CA

$97K - $133K/yr

Other

Posted 2 days ago

Cedars-Sinai rating

8.6

Company rating: 8.6 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

41st of 1,051 rated hospitals

Job description

Research Associate Data Scientist (Cedars-Sinai Medical Center; Los Angeles, CA): Assist with the development, evaluation, and application of computational and statistical methods, including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data. Assist with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications. Create database-to-deployment pipelines for models using the necessary programming languages (primarily Python, R, and C++). Create sustainable data science infrastructure and adheres to data analysis/machine learning best practices. Perform exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods. Work with senior or lead data scientists, research programmers, and principal investigators to identify areas where data science can best be applied to answer biomedical research questions. Test and validate code to ensure robustness of data applications. Perform all other duties as assigned. Participate in the development of innovative algorithms and analytical methods. Participate in the evaluation and interpretation of all analytical methods and results. Participate in the oral and written communication of scientific results including publications.

Minimum requirements: Master's degree or foreign equivalent in Electrical Engineering, Computer Science, Machine Learning, Applied Mathematics, Biomedical Imaging, or related field, plus three (3) years of experience as a Research Associate Data Scientist, Computer Engineer, Biomedical Data Scientist, or related occupation.

Must have experience with the following: Python, C++, and R; developing, testing, validating, and optimizing  production-level, version-controlled code (GitHub/GitLab and Azure DevOps) for algorithm development, statistical analysis, and deployment; implementing supervised and unsupervised learning algorithms (random forests, support vector machines, clustering, deep learning), with hands-on expertise training, fine-tuning, and deploying deep learning models using frameworks (PyTorch and TensorFlow), and adapting these methods to biomedical research problems; building end-to-end database-to-deployment pipelines including querying large relational databases (SQL), data cleaning, model training, validation, and deploying models in multiple computing environments; communicating scientific results effectively through peer-reviewed publications, patents, conference presentations, and internal technical reports; working with medical imaging data, including familiarity with industry-standard imaging formats (DICOM), image preprocessing workflows (segmentation, denoising, registration, resampling, and normalization), and use of imaging software libraries (SimpleITK, MONAI, or NiBabel) to prepare data for machine learning analysis; managing, processing, and optimizing large-scale 3D and 4D time-series datasets for deep learning model development on High-Performance Computing (HPC) or cloud-based GPU clusters.

Salary: $97,510 - $133,100 per year

To Apply: Any interested applicant may click on the APPLY NOW button above to apply for this position. 

Job Req ID: 18558

  • Assists with the development, evaluation, and/or application of computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
  • Assists with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
  • Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL, neo4j).
  • Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
  • Performs data cleaning, quality control, and exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods
  • Assists research, senior research, and/or lead research data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
  • Tests and validates code to ensure robustness of data applications with version control through GitHub.

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