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Remote Science Jobs in Spring, TX (NOW HIRING)

Agilent

Field Application Scientist

Houston, TX · On-site +1

$105K - $175K/yr

Provide field-based & remote scientific engagement with customers in both pre/post-sales capacities; from focused 1:1 consultation, to product demonstrations, and applications-focused training ...

Amplity Health

Medical Science Liaison - CST

Katy, TX · On-site +1

These are remote field-based roles. Purpose of Role The Medical Science Liaison (MSL) is responsible for establishing a respected and valued presence with opinion leaders and researchers in the ...

Element Science

Accounts Receivable Specialist

Houston, TX · Remote

$19.25 - $25.50/hr

Element Science is seeking an Accounts Receivable Specialist to join our growing Revenue Cycle Management team. This is a fully remote position , with a preference for candidates located in the ...

Arva Intelligence

Modeling Scientist

Houston, TX · On-site +1

$100K - $160K/yr

Remote Base Salary Range : $100k - $160k base salary The Modeling Scientist is responsible for improving model traceability, uncertainty quantification, and predictive trustworthiness in Arva ...

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All JobsRemote Science JobsRemote Science Jobs in Spring, TX

Remote Science information

See Spring, TX salary details

$21.8K

$43.1K

$70.3K

How much do remote science jobs pay per year?

As of Jun 19, 2026, the average yearly pay for remote science in Spring, TX is $43,063.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,300.00 and $46,300.00 per year, depending on experience, location, and employer.

What job makes $10,000 a month without a degree?

Remote science-related roles such as freelance data scientists, scientific consultants, or specialized research analysts can earn $10,000 or more per month without a formal degree, often by leveraging skills in programming, data analysis, and scientific tools. Success in these roles typically depends on experience, portfolio, and expertise rather than formal education alone.

What are some common challenges faced by professionals working in remote science roles, and how can they be addressed?

Professionals in remote science roles often face challenges such as effective communication across time zones, limited access to lab equipment, and maintaining collaboration with team members. To address these issues, it is helpful to establish regular virtual check-ins, utilize collaborative digital tools, and set clear expectations for project milestones. Many teams also adopt cloud-based data sharing and remote access to specialized software, ensuring that scientific work continues smoothly despite physical distance.

What is the difference between Remote Science vs Remote Data Analyst?

AspectRemote ScienceRemote Data Analyst
Required CredentialsScience degrees, research experience, technical skillsStatistics, data analysis certifications, technical skills
Work EnvironmentResearch labs, academic institutions, remote research projectsBusiness, finance, tech companies, remote data analysis roles
Employer & Industry UsageUniversities, research institutes, biotech firmsCorporations, consulting firms, tech startups
Search & Comparison IntentUnderstanding research roles, scientific projectsData analysis tasks, business insights

Remote Science and Remote Data Analyst roles share a focus on technical skills and remote work environments. However, Remote Science typically involves research, scientific experiments, and academic or biotech settings, while Remote Data Analysts focus on interpreting data for business insights in corporate environments. Both roles require analytical skills but differ in industry application and specific credentials.

Can you work remotely as a scientist?

Remote science jobs are available in various fields such as research, data analysis, and laboratory management, often requiring strong computer skills and familiarity with digital collaboration tools. Many organizations offer remote positions, but some roles may require on-site presence for experiments or equipment use. Job requirements vary depending on the specific scientific discipline and employer policies.

What are remote science jobs?

Remote science jobs are positions in scientific fields that can be performed outside of traditional laboratory or office environments, typically from home or any location with internet access. These jobs may include roles in research, data analysis, scientific writing, consulting, or education. Advances in technology and communication tools have made it possible for scientists to collaborate, conduct experiments, and analyze data remotely. Remote science jobs offer flexibility and can help employers and employees reach a broader talent pool. Common areas include biology, chemistry, environmental science, and healthcare research.

How can I make $100,000 a year working from home?

Remote science roles such as data scientists, research analysts, or scientific consultants can reach a $100,000 annual salary with advanced degrees, specialized skills, and experience. Building expertise in programming, statistical tools, and industry-specific knowledge, along with a strong professional network, can help achieve this income level while working remotely.

What are the key skills and qualifications needed to thrive as a Remote Science professional, and why are they important?

To thrive as a Remote Science professional, you need a strong background in your scientific discipline, analytical skills, and typically a relevant degree or higher qualification. Familiarity with data analysis tools, virtual collaboration platforms, and scientific software such as Python, R, or MATLAB is important. Excellent written communication, time management, and self-motivation are standout soft skills in this remote environment. These abilities ensure effective research, collaboration, and productivity while working independently from various locations.

Are there remote science jobs?

Yes, remote science jobs are available across various fields such as research, data analysis, and laboratory work. These roles often require strong technical skills, relevant certifications, and the ability to work independently in a virtual environment.
What are the most commonly searched types of Science jobs in Spring, TX? The most popular types of Science jobs in Spring, TX are:
What are popular job titles related to Remote Science jobs in Spring, TX? For Remote Science jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Remote Science jobs in Spring, TX look for? The top searched job categories for Remote Science jobs in Spring, TX are:
What cities near Spring, TX are hiring for Remote Science jobs? Cities near Spring, TX with the most Remote Science job openings:
Remote Science jobs near you
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Posted 16 days ago

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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