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Remote Neural Engineer Jobs in Houston, TX (NOW HIRING)

... and software engineering. Identifies patterns and looks for opportunities for optimization ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Remote Neural Engineer information

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$56.8K

$106.6K

$193.9K

How much do remote neural engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote neural engineer in Houston, TX is $106,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,900.00 and $126,500.00 per year, depending on experience, location, and employer.

What is a remote neural engineer?

A Remote Neural Engineer is a professional who designs, develops, and maintains neural engineering systems—such as brain-computer interfaces or neural prosthetics—while working remotely. They often collaborate with multidisciplinary teams to create solutions that interface with the nervous system, using expertise in neuroscience, biomedical engineering, and software development. Remote Neural Engineers may work from home or distributed locations, utilizing digital tools to analyze neural data, develop algorithms, and contribute to research or product development in the neural technology field.

What are the key skills and qualifications needed to thrive as a remote neural engineer, and why are they important?

To thrive as a Remote Neural Engineer, you need a solid background in neuroscience, biomedical engineering, or electrical engineering, often supported by a relevant degree or advanced certification. Proficiency with neural signal processing software, programming languages like Python or MATLAB, and brain-computer interface (BCI) systems is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are vital soft skills in this role. These skills and qualities are essential for developing, analyzing, and troubleshooting complex neural systems while collaborating with teams remotely.

How do remote neural engineers typically collaborate with cross-functional teams while working off-site?

Remote Neural Engineers frequently use digital collaboration tools such as video conferencing, shared code repositories, and project management platforms to stay connected with colleagues in neuroscience, software development, and data science. Regular virtual meetings and asynchronous communication help ensure alignment on project goals, data analysis, and protocol development. This structure allows for flexibility, but also requires proactive communication and strong organizational skills to manage complex, interdisciplinary tasks from a distance.

What is the difference between Remote Neural Engineer vs Remote Data Scientist?

AspectRemote Neural EngineerRemote Data Scientist
Required CredentialsDegree in neuroscience, biomedical engineering, or related fields; knowledge of neural interfacesDegree in computer science, statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch labs, tech companies, healthcare institutions with focus on neural dataTech firms, finance, healthcare, analyzing large datasets
Industry UsageNeuroscience, biomedical engineering, neurotechnologyTechnology, finance, healthcare, research
Common Search/ComparisonYesYes

Remote Neural Engineers focus on developing and implementing neural interfaces and understanding neural systems, often requiring knowledge of neuroscience and biomedical engineering. Remote Data Scientists analyze large datasets to extract insights, typically with skills in statistics and programming. While both roles involve technical expertise and data analysis, Neural Engineers are more specialized in neural technologies, whereas Data Scientists have a broader application across industries.

How much money do remote neural engineers make?

Remote neural engineers typically earn between $80,000 and $150,000 annually, depending on experience, education, and the complexity of projects. Senior professionals with specialized skills in neural signal processing and machine learning can earn higher salaries, especially when working for research institutions or tech companies.

Is remote neural engineering a good career?

Remote neural engineering is a specialized field involving the development of brain-computer interfaces and neural signal processing, often requiring expertise in neuroscience, engineering, and programming. It offers opportunities in research, healthcare, and technology sectors, with a growing demand for skilled professionals due to advances in neurotechnology and remote collaboration tools.

What are the most commonly searched types of Neural Engineer jobs in Houston, TX?

The most popular types of Neural Engineer jobs in Houston, TX are:

What are popular job titles related to Remote Neural Engineer jobs in Houston, TX?

For Remote Neural Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Remote Neural Engineer jobs in Houston, TX look for?

The top searched job categories for Remote Neural Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Remote Neural Engineer jobs?

Cities near Houston, TX with the most Remote Neural Engineer job openings:

Lead Data Scientist

MaxIT Consulting - Max Corporate Group

Houston, TX • Remote

Full-time

Posted 4 days ago


Key responsibilities

  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.

  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.

  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.


Job description

Lead Data Scientist

United States | Remote within GA, LA, OK, TN or TX | Direct Hire

The Opportunity

A large healthcare organization is seeking an experienced Lead Data Scientist to lead advanced analytics initiatives involving complex structured and unstructured data.

This role combines hands-on data science, statistical modeling, machine learning, stakeholder engagement, and technical leadership. The successful candidate will partner with cross-functional teams to translate complex business challenges into analytical solutions and deliver actionable insights that support data-driven decision-making.

The position reports to the Manager of Data Science and includes responsibility for leading high-priority projects, mentoring other data scientists, and presenting analytical findings to senior leadership.

Key Responsibilities
  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.
  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.
  • Develop custom data models and algorithms to address business questions and improve operational performance.
  • Build and apply predictive models and analytical approaches to key business metrics.
  • Conduct research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
  • Develop and test hypotheses and translate findings into clear, actionable recommendations.
  • Maintain existing analytical models and evaluate model performance and goodness of fit.
  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.
  • Identify, investigate, and resolve complex data quality and data availability issues.
  • Improve the efficiency, scalability, and reliability of data processes.
  • Manage multiple small and medium-sized analytical engagements and competing priorities.
  • Provide technical guidance, coaching, and mentoring to other data scientists.
  • Help educate broader audiences on data science capabilities, techniques, and developments.
  • Communicate complex analytical concepts to both technical and non-technical stakeholders.
  • Present analytical findings and recommendations to senior leadership.
  • Assist in evaluating data science tools, platforms, and vendors.
Required Qualifications
  • Bachelor's Degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another related STEM discipline.
  • Minimum of 7 years of professional Data Science experience.
  • Strong business analytical capabilities, including process analysis, modeling, spreadsheets, procedures, and analytical problem-solving.
  • Strong understanding of data architecture and design principles.
  • Advanced analytical reasoning, problem-solving, and decision-making skills.
  • Demonstrated ability to independently investigate complex problems and identify the information necessary to reach sound conclusions.
  • Ability to manage multiple initiatives with competing priorities while meeting project goals and deadlines.
  • Excellent written and verbal communication skills.
  • Ability to explain complex technical and analytical information to both technical and business audiences.
  • Strong stakeholder management and client-facing capabilities.
  • Ability to work independently with minimal supervision in a fast-paced, multidisciplinary environment.
  • Strong ability to troubleshoot issues, recommend solutions, and manage challenging stakeholder situations.
Required Technical & Analytical Experience

Candidates should demonstrate strong practical knowledge of:

  • Machine learning techniques, including:
    • Clustering
    • Decision tree learning
    • Artificial neural networks
    • Understanding of the practical advantages and limitations of different modeling approaches
  • Advanced statistical techniques and concepts, including:
    • Regression
    • Statistical distributions
    • Statistical testing
    • Time series forecasting
    • A/B testing
    • Clustering
  • Predictive modeling and advanced analytics.
  • Data mining, visualization, and pattern analysis.
  • Advanced SQL and database management tools.
  • Programming for analytical and data science applications.
  • Statistical analysis tools.
  • The full data science project lifecycle.
  • Analysis of large, complex, and incomplete data sources.
  • Model evaluation and interpretation of analytical results.
Leadership & Stakeholder Management

The ideal candidate will be able to combine technical depth with strong business communication.

The role requires the ability to:

  • Translate complex data into meaningful business insights.
  • Gather requirements directly from stakeholders.
  • Build compelling, evidence-based data stories.
  • Present findings confidently to senior and executive leadership.
  • Lead cross-functional analytical initiatives.
  • Mentor and provide technical guidance to less experienced data science professionals.
  • Translate complex findings into clear recommendations for a broad range of stakeholders.
Preferred Experience

The following experience is preferred but not required:

  • Master's Degree in Data Science.
  • Professional experience within a hospital or healthcare environment.
  • Medical informatics.
  • Healthcare information technology.
  • Healthcare finance or revenue cycle data management.
  • Electronic Health Record (EHR) data management.
Candidate Profile

The strongest candidate will combine advanced quantitative expertise with strong business judgment and communication skills.

They should be comfortable moving from raw and incomplete data through statistical analysis and modeling, identifying meaningful insights, and ultimately presenting those findings in a concise and actionable manner to senior stakeholders.

A strong analytical mindset, executive-level communication capability, project ownership, and the ability to mentor others are important for success in this position.

Work Arrangement

This opportunity is remote, but candidates must be able to work from one of the following states:

  • Georgia
  • Louisiana
  • Oklahoma
  • Tennessee
  • Texas

Travel of up to 20% may be required.

Work Authorization

Some visa sponsorship arrangements may be supported for this opportunity. Eligibility should be evaluated based on the individual candidate's circumstances.