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Remote Data Collection Driver Jobs in Texas (NOW HIRING)

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... Experience in one or more of the following areas: machine learning tasks, data collection and ...

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... Experience in one or more of the following areas: machine learning tasks, data collection and ...

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Remote Data Collection Driver information

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 Texas? The most popular types of Data Collection Driver jobs in Texas are:
What are popular job titles related to Remote Data Collection Driver jobs in Texas? For Remote Data Collection Driver jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Remote Data Collection Driver jobs in Texas look for? The top searched job categories for Remote Data Collection Driver jobs in Texas are:
What cities in Texas are hiring for Remote Data Collection Driver jobs? Cities in Texas with the most Remote Data Collection Driver job openings:
Remote Data Collection Driver jobs near you

Senior Python Data Scraping Engineer (Freelance)

Mindrift

Dallas, TX • Remote

$45/hr

Part-time

Posted 7 days ago

Job description

Mindrift is looking for highly skilled Senior Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.

In this role, as an AI Pilot - that's how we refer to this role at Mindrift - you'll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.

This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.

What We Do

The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.

This is a freelance role for a Tendem project. As a Senior Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.

Key Responsibilities:

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.
  • Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.
  • Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
  • Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

Requirements:

  • At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).
  • Bachelor's or Master's Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.
  • Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows. We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.
  • Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies
  • Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML)
  • Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets)
  • Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale
  • Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows
  • Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks
  • Strong attention to detail and commitment to data accuracy
  • Self-directed work ethic with ability to troubleshoot independently
  • A link to GitHub is a plus
  • English proficiency: Upper-intermediate (B2) or above (required)

Project time expectations

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

Compensation

On this project, contributors can earn up to $45 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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