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Remote Data Collection Driver Jobs in California

This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and ... Building tools to automate data collection * Develop custom data models and algorithms to apply to ...

San Francisco, CA About the Role HumanSignal specializes in operationally complex, multimodal data collection and annotation -- delivering the datasets that frontier AI research requires and remote ...

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Experience with psychophysiological data collection or analysis (e.g., Biopac , LSL , EDA, EMG, HR/HRV, facial coding, or remote PPG from video) is strongly preferred ; enthusiasm for further ...

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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 California? The most popular types of Data Collection Driver jobs in California are:
What are popular job titles related to Remote Data Collection Driver jobs in California? For Remote Data Collection Driver jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Remote Data Collection Driver jobs? Cities in California with the most Remote Data Collection Driver job openings:

Data Scientist II

CorVel Corporation

Irvine, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


CorVel rating

7.9

Company rating: 7.9 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

82nd of 138 rated financial services


Job description

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.

Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.

The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.

Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.

This position is open to remote or hybrid.

ESSENTIAL FUNCTIONS & RESPONSIBILITIES:

  • Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
  • Creating new, experimental frameworks to collect data
  • Building tools to automate data collection
  • Develop custom data models and algorithms to apply to data sets
  • Design, build, train, and deploy machine learning models and data products for enterprise use
  • Translate business and operational needs into scalable data science solutions and modeling approaches
  • Perform feature engineering, data preparation, and exploratory analysis to support model development
  • Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
  • Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
  • Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
  • Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
  • Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
  • Perform model validation, testing, and documentation to ensure quality and reproducibility
  • Contribute to technical design discussions and provide input on architecture and implementation strategies
  • Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
  • Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
  • Develop A/B testing framework and test model quality
  • Passion for technology and emerging AI/ML trends
  • Additional duties as assigned

KNOWLEDGE & SKILLS:

  • Strong problem-solving skills with an emphasis on product development.
  • Strong foundation in machine learning, statistical modeling, and data science techniques
  • Experience building and deploying machine learning models in production environments
  • Familiarity with modern AI approaches, including:
    • Natural language processing (NLP)
    • Large language models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Feature engineering and model evaluation techniques
  • Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
  • Familiarity with data pipelines, APIs, and integration patterns
  • Proficiency in programming languages such as Python and database management including SQL
  • Strong problem-solving skills with the ability to structure complex problems into analytical solutions
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
  • Excellent presentation and written/verbal communication skills

EDUCATION & EXPERIENCE:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred
  • 2–5+ years of experience in data science, machine learning, or related roles
  • Experience developing and deploying machine learning models in production environments
  • Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
  • Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
  • Experience working within enterprise software environments and SDLC practices preferred

PAY RANGE:

CorVel uses a market based approach to pay and our salary ranges may vary depending on your location.  Pay rates are established taking into account the following factors:  federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions.  Our ranges may be modified at any time.

For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role.  The level may impact the salary range and these adjustments would be clarified during the offer process.

Pay Range:  $82,574 – $127,490

A list of our benefit offerings can be found on our CorVel website: CorVel Careers | Opportunities in Risk Management

In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.

About CorVel

CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries.   CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients.  We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities.  Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off.

CorVel is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.

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