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Remote Data Analysis Jobs in Spring, TX (NOW HIRING)

Enverus

Data Specialist - 26327

Houston, TX · Remote

By offering anytime, anywhere access to analytics and insights, we're helping our customers make ... We are currently recruiting for a Data Specialist to join our organization; this is a remote ...

YO AI Labs

AI Consulting Expert - Remote

Houston, TX · Remote

$100 - $200/hr

No prior AI experience is required--your consulting expertise, analytical thinking, and ... Annotate data, interpret findings, and perform fact-checking to ensure high-quality content.

micro1 AI

Cheminformatics Specialist - Remote

Conroe, TX · On-site +1

$90 - $120/hr

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

micro1 AI

Cheminformatics Specialist - Remote

Houston, TX · On-site +1

$90 - $120/hr

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

micro1 AI

Cheminformatics Specialist - Remote

Pasadena, TX · On-site +1

$90 - $120/hr

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

The Bergaila Companies

Remote Field Operator

Spring, TX · On-site +1

Familiarity with remote monitoring technology and data analysis tools Preferred Education and Experience: * High school diploma or equivalent; technical certifications preferred * Minimum of 3+ years ...

Papco

Energy Procurement Analyst

Houston, TX · Remote

Remote (U.S.) About World Fuel At World Fuel, we help commercial and industrial customers navigate ... Data Analysis & Process Management * Maintain accurate customer portfolio information and validate ...

DataAnnotation

FP&A Manager - AI Trainer

Conroe, TX · Remote

$50 - $100/hr

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

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Showing results 21-40

All JobsData Analysis JobsRemote Data Analysis JobsRemote Data Analysis Jobs in Spring, TX

Remote Data Analysis information

What is remote data analysis?

Remote data analysis refers to the process of examining, interpreting, and drawing insights from data using digital tools, while working from a location outside of a traditional office setting. Professionals in this field utilize statistical software, databases, and visualization tools to analyze large datasets and help organizations make informed decisions. Remote data analysts often collaborate with team members and stakeholders virtually, ensuring that data-driven strategies are implemented effectively. This role requires strong analytical skills, attention to detail, and the ability to communicate findings clearly.

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, statistical knowledge, and a background in fields like mathematics, statistics, or computer science. Proficiency with data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management help remote analysts present insights clearly and stay productive without direct supervision. These skills and qualities ensure accurate data-driven decisions and effective remote collaboration with stakeholders.

How do remote data analysts typically collaborate with team members and stakeholders?

Remote data analysts often use a combination of communication and project management tools—such as Slack, Microsoft Teams, and Zoom—to stay connected with colleagues and stakeholders. Regular virtual meetings, shared dashboards, and collaborative platforms enable them to discuss findings, gather requirements, and provide updates on ongoing projects. Clear documentation and proactive communication are essential to ensure alignment, especially when working across different time zones or departments. Building strong relationships with team members virtually can help streamline workflows and facilitate effective decision-making.

What is the difference between Remote Data Analysis vs Remote Data Entry?

AspectRemote Data AnalysisRemote Data Entry
Required SkillsData interpretation, statistical tools, analytical skillsTyping speed, accuracy, basic computer skills
Tools UsedExcel, SQL, data visualization softwareSpreadsheets, data entry platforms
Work EnvironmentAnalytical tasks, report creation, data insightsData input, database updating, record management
Common CertificationsData analysis certifications, Excel proficiencyNone typically required

Remote Data Analysis involves interpreting data, creating reports, and providing insights using analytical tools, while Remote Data Entry focuses on inputting and managing data accurately. Both roles are performed remotely and require computer skills, but Data Analysis demands analytical expertise and familiarity with data tools, whereas Data Entry emphasizes speed and accuracy in data input tasks.

Can I get a remote job as a remote data analyst?

Remote data analyst positions are widely available and often require skills in data visualization, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Many companies offer remote roles with flexible schedules, and a strong portfolio or certification can improve job prospects.

Is data analysis a good career for remote work?

Data analysis is well-suited for remote work because it primarily involves computer-based tasks such as working with datasets, using tools like Excel, SQL, and Python, and communicating insights through reports. Many companies offer remote data analyst positions, and strong skills in data visualization and self-management are important for success in a remote environment.

What are the most commonly searched types of Data Analysis jobs in Spring, TX?

The most popular types of Data Analysis jobs in Spring, TX are:

What are popular job titles related to Remote Data Analysis jobs in Spring, TX?

For Remote Data Analysis jobs in Spring, TX, the most frequently searched job titles are:

What job categories do people searching Remote Data Analysis jobs in Spring, TX look for?

The top searched job categories for Remote Data Analysis jobs in Spring, TX are:

What cities near Spring, TX are hiring for Remote Data Analysis jobs?

Cities near Spring, TX with the most Remote Data Analysis job openings:

Remote Data Analysis jobs near you
Infographic showing various Remote Data Analysis job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Re-posted 20 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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