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Field Data Collection Jobs in California (NOW HIRING)

Hark

Data Collection

San Jose, CA · On-site

$150K - $250K/yr

About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ... field. Bonus Qualifications * Experience managing human feedback or preference data programs.

Hark

Data Collection

San Jose, CA

$150K - $250K/yr

About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ... field. Bonus Qualifications * Experience managing human feedback or preference data programs.

TSMG

Driver/Data Collector in Modesto, CA

Modesto, CA · On-site

Field Data Collection Project Service Measure (SM) is a field data collection company founded in 2013 in New York. We collect data where automation is not possible. We count features, take pictures ...

TSMG

Field Surveyor (public transport)

San Diego, CA · On-site

Company Description Service Measure (SM) is a field data collection company founded in 2013 in New York. We collect data where automation is not possible. We count features, take pictures, make ...

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How much do field data collection jobs pay per hour?

As of Aug 4, 2026, the average hourly pay for field data collection in California is $21.94, according to ZipRecruiter salary data. Most workers in this role earn between $16.71 and $23.30 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a field data collection specialist, and why are they important?

To thrive as a Field Data Collection Specialist, you need keen observational skills, attention to detail, and a background in data gathering or research, often supported by a relevant degree or training. Familiarity with mobile data collection tools, GPS devices, and survey software is typically required. Strong communication, adaptability, and problem-solving abilities help you interact effectively with participants and handle unexpected challenges in the field. These skills ensure accurate, high-quality data collection that supports reliable research outcomes.

What are some common challenges faced in a field data collection role, and how can they be managed?

Field Data Collection professionals often encounter challenges such as unpredictable weather, difficult terrain, or uncooperative respondents. Effective time management, careful planning, and adaptability are essential for overcoming these obstacles. Building strong communication skills helps in gaining respondents’ trust, while proficiency with data collection tools ensures accuracy and efficiency. Many organizations provide orientation or training to help new hires prepare for these field-specific challenges.

What is the difference between Field Data Collection vs Field Survey Technician?

AspectField Data CollectionField Survey Technician
CredentialsMay require certifications in data management or GISTypically requires survey or civil engineering certifications
Work EnvironmentOutdoor, on-site data gathering across various industriesOutdoor, focused on land or infrastructure surveys
Industry UsageUsed across research, environmental, and utility sectorsPrimarily in construction, civil engineering, and land development
Job FocusCollecting, recording, and managing data in the fieldConducting land surveys, measurements, and mapping

Field Data Collection involves gathering and managing data in various industries, often requiring data management skills. Field Survey Technicians focus on land and infrastructure surveys, with specialized surveying certifications. While both roles operate outdoors and require fieldwork, their specific tasks and industry applications differ.

What is field data collection?

Field data collection is the process of gathering raw information or measurements directly from a physical location, rather than from secondary sources or databases. This work is often done in industries like environmental science, market research, agriculture, and public health, where accurate, firsthand data is crucial. Field data collectors may use surveys, interviews, observations, or specialized equipment to record information in the field. The collected data is then analyzed to support research, policy decisions, or business strategies.
What are popular job titles related to Field Data Collection jobs in California? For Field Data Collection jobs in California, the most frequently searched job titles are:
What job categories do people searching Field Data Collection jobs in California look for? The top searched job categories for Field Data Collection jobs in California are:
What cities in California are hiring for Field Data Collection jobs? Cities in California with the most Field Data Collection job openings:
Field Data Collection jobs near you
Infographic showing various Field Data Collection job openings in California as of July 2026, with employment types broken down into 2% Internship, 55% Full Time, 35% Part Time, 2% Temporary, and 6% Contract. Highlights an 98% In-person, and 2% Hybrid job distribution, with an average salary of $45,633 per year, or $21.9 per hour.

Data Collection

Hark

San Jose, CA • On-site

$150K - $250K/yr

Full-time

Re-posted 18 days ago

Job description

About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
About the Role
You'll own data collection at Hark - the programs, the vendors, and the pipelines that turn raw signal into training data our models can actually learn from.
That means running end-to-end campaigns across human feedback, synthetic data, and product-embedded signals. The quality of what we collect shapes the quality of what we ship, and this role owns that loop.
This is a high-ownership role on a small team. You'll work directly with researchers, engineers, and external partners, and the data you deliver will directly influence how our models behave in the real world.
Responsibilities
  • Design and run data collection programs end-to-end - scoping requirements, writing instructions, defining success criteria, and driving execution with vendors and annotators.
  • Manage external vendor relationships. Be the primary interface between Hark and data partners, keeping quality high and timelines on track.
  • Assess collected data using internal tooling, identify quality issues, and feed clear, actionable feedback back to vendors and annotators.
  • Collaborate closely with model researchers and engineers to understand what data is needed, translate that into operational plans, and deliver.
  • Track program metrics, surface insights, and drive continuous improvements to quality, throughput, and process.
  • Identify gaps in tooling and workflows and propose concrete improvements.

Requirements
  • Operational excellence. You can manage multiple programs simultaneously, keep track of details under pressure, and bring structure to fast-moving situations.
  • Experience working with external vendors or contractors. You know how to set expectations, manage relationships, and hold partners accountable to quality.
  • A knack for data. You've gone beyond surface-level metrics - you dig in, find patterns, and use what you find to make things better.
  • Strong communication. You can translate between research requirements and operational reality, and you keep everyone aligned without letting things slip.
  • Comfort with ambiguity and fast iteration. You take a rough problem, build a process around it, get feedback, and tighten it quickly.
  • Genuine curiosity about AI. You don't need to be an ML researcher, but you care about how models learn and why data quality matters.
  • 2+ years of relevant experience in data operations, program management, or a related field.

Bonus Qualifications
  • Experience managing human feedback or preference data programs.
  • Familiarity with data annotation platforms or labeling pipelines.
  • Experience with synthetic data generation or evaluation dataset design.
  • Background working at a fast-moving AI or research-driven company.

Compensation
The US base salary range for this full-time position is between $150,000 - $250,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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