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How much do data science neuroscience jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data science neuroscience in the United States is $111,898.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $156,000.00 per year, depending on experience, location, and employer.

How do data scientists in neuroscience typically collaborate with research teams and clinicians?

Data scientists in neuroscience often work closely with multidisciplinary teams that include neuroscientists, clinicians, and other data specialists. They are responsible for designing and implementing analytical pipelines, interpreting complex brain data, and translating findings into actionable insights for both research and clinical applications. Effective communication skills are crucial, as they must explain technical results to non-technical team members and adapt analyses based on evolving research questions. This collaborative environment offers opportunities to contribute to cutting-edge discoveries and impacts both academic and medical advancements.

Can I become a data science neuroscientist with a neuroscience degree?

A neuroscience degree provides a strong foundation for a data science neuroscientist role, but additional skills in programming, statistics, and data analysis are typically required. Gaining experience with tools like Python, R, and machine learning, along with relevant certifications or coursework, can enhance eligibility for this interdisciplinary position.

What are the key skills and qualifications needed to thrive as a data science neuroscience professional, and why are they important?

To excel as a Data Science Neuroscience professional, you need a strong background in neuroscience, statistics, and programming, often supported by an advanced degree in neuroscience, data science, or a related field. Familiarity with data analysis tools such as Python, R, MATLAB, machine learning frameworks, and neuroimaging software like SPM or FSL is typically required. Critical thinking, problem-solving, and the ability to communicate complex findings clearly make individuals stand out in this interdisciplinary role. These skills are vital for effectively analyzing large-scale neural data, generating insights, and facilitating collaboration between data scientists and neuroscientists.

What is data science in neuroscience?

Data Science in Neuroscience involves applying computational, statistical, and analytical methods to study the brain and nervous system. Data scientists in this field analyze large-scale datasets, such as brain imaging, genomic, or behavioral data, to uncover patterns and insights about neural function and disorders. They use machine learning, data visualization, and other quantitative tools to advance understanding of the brain, support research, and aid in clinical decision-making. This interdisciplinary role requires knowledge of neuroscience, computer science, and statistics.
What cities are hiring for Data Science Neuroscience jobs? Cities with the most Data Science Neuroscience job openings:
What are the most commonly searched types of Data Science Neuroscience jobs? The most popular types of Data Science Neuroscience jobs are:
What states have the most Data Science Neuroscience jobs? States with the most job openings for Data Science Neuroscience jobs include:
Infographic showing various Data Science Neuroscience job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $111,898 per year, or $53.8 per hour.

Research Scientist I, Moody Brain Health Institute

UTMB Health

Galveston, TX

Full-time

Re-posted yesterday


UTMB Health rating

7.3

Company rating: 7.3 out of 10

Based on 168 frontline employees who took The Breakroom Quiz

268th of 887 rated healthcare providers


Job description

JOB SUMMARY

The Research Scientist will lead research and development focused on digital twin modeling for brain health and health trajectory prediction within the Moody Brain Health Institute. This role involves designing, implementing, and validating computational models that simulate individual brain and health states across the lifespan. The scientist will integrate multi-modal patient data, including neuroimaging, electrophysiology, genomics, digital biomarkers, and electronic health records (EHRs), to create predictive digital twins capable of informing early diagnosis, personalized interventions, and resilience modeling. The position combines data science, neuroscience, and translational health research to advance precision brain health. They will also contribute to development of grant proposals, and scholarly publications.

ESSENTIAL JOB FUNCTIONS

·         Execute the core’s research initiatives, advancing key projects and objectives.

·         Design and implement predictive models based on patient data to support research and clinical applications.

·         Lead the development of virtual patient models to advance personalized medicine and data-driven research.

·         Develop comprehensive data extraction strategies for Electronic Health Record (EHR) data, ensuring efficient and accurate analysis.

·         Integrate multi-scale data sources such as neuroimaging, omics, cognitive, behavioral, and EHR data to build comprehensive individual-level representations.

·         Present research findings and core activities at both internal and external conferences, symposia, and workshops.

·         Support grant applications and publications, highlighting innovations in digital twin technologies for brain health.

·         Contribute to infrastructure planning, including computing resources, secure data management, and AI model governance.

·         Partner with the core director to plan resources and training for the development of AI tools and technologies.

KNOWLEDGE/SKILLS/ABILITIES

·         Excellent communication and interpersonal skills with a high degree of professionalism. 

·         Experience with high-throughput data analysis.

·         Proficiency in AI, deep learning, and data fusion techniques for multimodal health data.

·         Familiarity with federated or privacy-preserving learning for healthcare applications.

·         Excellent communication and collaboration skills, with the ability to convey complex bioinformatics concepts to non-experts.

·         Strong analytical skills and a proactive approach to problem resolution.

·         Excellent decision-making skills.

EDUCATION & EXPERIENCE

Minimum Qualifications:

·         PhD in Bioinformatics, Data Science, Biomedical Informatics, or a related biomedical field.

·         Proven experience in Artificial Intelligence and/or statistical modeling,

·         Familiarity with EHR data extraction, and analysis.

·         Excellent communication skills and ability to collaborate with interdisciplinary teams.

Preferred Qualifications:

·         Experience in working with AI and machine learning models, particularly in the biomedical context.

·         Experience in digital twin frameworks, personalized modeling, or health trajectory prediction.

·         Proven ability to lead collaborative, data-driven projects across disciplines.

·         Prior involvement in leading or managing research projects.


SALARY:
Commensurate with experience. 
 

EQUAL EMPLOYMENT OPPORTUNITY:
UTMB Health strives to provide equal opportunity employment without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, genetic information, disability, veteran status, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. As a Federal Contractor, UTMB Health takes affirmative action to hire and advance protected veterans and individuals with disabilities.


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