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Remote Data Collection Driver Jobs in Houston, TX

Wood Plc

GIS Analyst - FEMA

Houston, TX · Remote

Customize GIS workflow and software programs for data collection, engineering, and environmental applications #LI-Remote Skills / Qualifications Required: * 2 - 5 years of GIS project experience * BA ...

Crescent Energy

Air Quality Specialist II

Houston, TX · On-site +1

... collection and submissions for sources on Indian reservations (e.g., Uintah and Ouray) * Lead ... Proficiency in Microsoft Office, ProMax modeling, data analysis, and oil/gas production or remote ...

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All JobsRemote Data Collection Driver JobsRemote Data Collection Driver Jobs in Houston, TX

Remote Data Collection Driver information

See Houston, TX salary details

$15

$24

$30

How much do remote data collection driver jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for remote data collection driver in Houston, TX is $24.17, according to ZipRecruiter salary data. Most workers in this role earn between $22.26 and $24.81 per hour, depending on experience, location, and employer.

What is the difference between Remote Data Collection Driver vs Field Data Collector?

AspectRemote Data Collection DriverField Data Collector
CredentialsDriver's license, possibly a background checkSimilar credentials, often including a valid driver's license
Work EnvironmentPrimarily remote, traveling between locations, often using a vehicleOn-site at data collection points, often in various field locations
Employer & IndustryResearch firms, survey companies, market researchResearch organizations, government agencies, market research

The Remote Data Collection Driver and Field Data Collector roles share similarities in credentials and industry usage. The main difference lies in the work environment: Remote Data Collection Drivers primarily travel between locations using a vehicle, often working remotely, while Field Data Collectors typically work on-site at specific locations. Both roles are essential for gathering data in research and market analysis, but their daily tasks and settings differ significantly.

What are some common challenges faced by Remote Data Collection Drivers, and how can they be addressed?

Remote Data Collection Drivers often encounter challenges such as navigating unfamiliar routes, dealing with varied weather conditions, and ensuring data accuracy while on the move. To overcome these, drivers should familiarize themselves with route planning tools, maintain regular communication with their support team, and follow best practices for data verification. Staying organized and proactive helps ensure data is collected efficiently and safely, and most companies provide training and support to help drivers handle these challenges.

What are Remote Data Collection Drivers?

Remote Data Collection Drivers are professionals who operate vehicles equipped with specialized sensors or devices to gather data for various purposes, such as mapping, traffic analysis, or infrastructure assessment. Unlike traditional drivers, their primary responsibility is to follow predetermined routes while ensuring accurate data collection, often working independently and reporting findings digitally. This role may include using GPS equipment, cameras, or other technology to record information, and it often allows for flexible or remote scheduling. Remote Data Collection Drivers are typically employed by companies involved in geographic information systems (GIS), urban planning, or autonomous vehicle development.

What are the key skills and qualifications needed to thrive as a Remote Data Collection Driver, and why are they important?

To thrive as a Remote Data Collection Driver, you need a valid driver's license, a clean driving record, and strong navigation skills, often supported by familiarity with GPS and mapping technologies. Proficiency with mobile data collection devices, onboard cameras, and reporting software is typically required. Attention to detail, reliability, and strong time management help ensure accurate data collection and adherence to schedules. These skills are crucial for safely and efficiently gathering high-quality geographic or survey data to support organizational needs.
What are the most commonly searched types of Data Collection Driver jobs in Houston, TX? The most popular types of Data Collection Driver jobs in Houston, TX are:
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What cities near Houston, TX are hiring for Remote Data Collection Driver jobs? Cities near Houston, TX with the most Remote Data Collection Driver job openings:
Remote Data Collection Driver jobs near you
Data Scientist - Remote

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

Posted yesterday

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

Sourced by ZipRecruiter

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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