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Online Data Labelling Jobs (NOW HIRING)

Data Scientist II

Chicago, IL · On-site +1

$130K - $150K/yr

Build measurement and evaluation frameworks -- both offline and online -- to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Build measurement and evaluation frameworks - both offline and online - to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Build measurement and evaluation frameworks - both offline and online - to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Build measurement and evaluation frameworks -- both offline and online -- to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

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Online Data Labelling information

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$46K

$165K

$243.5K

How much do online data labelling jobs pay per year?

As of Jul 13, 2026, the average yearly pay for online data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Online Data Labelling vs Data Annotation?

AspectOnline Data LabellingData Annotation
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexibleRemote or in-office, depending on project
Industry UsageCommon in AI/ML data preparationUsed across AI, computer vision, NLP projects
Search IntentOnline Data Labelling vs Data Annotation

Online Data Labelling and Data Annotation are closely related roles in AI data preparation. While both involve labeling data for machine learning, Online Data Labelling often emphasizes quick, online tasks, whereas Data Annotation may include more detailed, specialized labeling. Both roles are essential in training AI models and share similar skills and work environments.

What is online data labelling?

Online data labelling is the process of tagging or annotating data—such as images, text, or audio—using digital tools to make it understandable for machine learning algorithms. Data labelers review raw data and apply predefined labels to help train artificial intelligence systems, enabling them to recognize patterns and make predictions. This work is essential for improving the accuracy and performance of AI models in various applications, such as image recognition, natural language processing, and autonomous vehicles. Online data labelling jobs are often remote and require attention to detail, consistency, and sometimes domain-specific knowledge.

What are some common challenges faced by online data labelers, and how can they be managed effectively?

Online data labelers often encounter challenges such as repetitive tasks, strict accuracy requirements, and tight deadlines. Maintaining high attention to detail is crucial, as even small errors can impact the quality of machine learning models. To manage these challenges, it's helpful to take regular breaks, use productivity tools, and communicate any ambiguities or unclear instructions with supervisors or team leads. Many organizations also offer support channels and quality assurance feedback to help labelers continuously improve their work.

What are the key skills and qualifications needed to thrive as an Online Data Labeller, and why are they important?

To excel as an Online Data Labeller, you need strong attention to detail, basic data handling skills, and familiarity with data annotation protocols, often requiring at least a high school diploma. Proficiency with data labelling platforms such as Labelbox, Supervisely, or Scale AI, and sometimes knowledge of spreadsheet tools, is typically necessary. Reliability, consistency, and the ability to follow detailed guidelines make individuals stand out in this role. These skills ensure high-quality, accurately labelled datasets that are critical for training effective AI and machine learning models.
More about Online Data Labelling jobs
What cities are hiring for Online Data Labelling jobs? Cities with the most Online Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Online Data Labelling jobs? States with the most job openings for Online Data Labelling jobs include:
Infographic showing various Online Data Labelling job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Clinical Research Coordinator

Clinical Research Coordinator

University of California San Francisco

San Francisco, CA • On-site

$28.50 - $38/hr

Full-time

Re-posted 21 hours ago


University Of California San Francisco rating

8.9

Company rating: 8.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

31st of 553 rated colleges and universities


Job description

The Clinical Research Coordinator (CRC) will perform independently or with general direction at the fully operational journey level of the series to execute, manage, and coordinate research protocols, as directed by the Clinical Research Supervisor and/or Principal Investigator (PI); may coordinate the data collection and operations of several concurrent clinical research studies under the guidelines of research protocols, UCSF and regulating agency policies. 

The CRC will coordinate various clinical studies on kidney disease patients. Duties include: enrolling patients in and assisting with execution of 1) industry trials for kidney disease; 2) enrollment of patients in biospecimen banking study from kidney disease clinic; 3) various smaller pilot studies in clinic 4) maintaining IRBs; and 5) other research studies as time permits. Responsibilities for all studies include: schedule patient visits and procedures; maintain accurate research charts and research study binders; perform accurate data collection and data entry; perform patient follow-up visits according to specific research study requirements; complete consent procedures and questionnaires with subjects; participate in research meetings; manage Investigator's protocols in the Committee on Human Research (IRB) online system, as well as renewals and modifications of protocol applications and the implementation of new studies; participate in the review and writing of protocols to ensure institutional review board approval within University compliance; help assure compliance with all relevant regulatory agencies; oversee study data integrity; implement and maintain periodic quality control procedures; interface with departments to obtain UCSF approval prior to study initiation; maintain all regulatory documents; report study progress to investigators; participate in any internal and external audits or reviews of study protocols; and perform other duties as assigned.  Also responsible for creating research accounts in Apex; linking patients to the research study and keeping their research status updated; linking encounters to the study and setting the research billing flag; creating lab orders and medication orders in Apex; scanning and uploading study consent forms into the patient's medical chart; reviewing lab results, current medications, radiology studies, and providers' progress notes for data collection into the research study database. The incumbent will also be required to create and maintain data entry accounts in Redcap and OnCore, the online data entry systems for research. Perform other duties as needed. There may be other opportunities to assist with other studies within the Division of Nephrology.  If the incumbent is a certified phlebotomist, perform phlebotomy as needed. 

Required Qualifications:

  • HS graduation and sufficient experience and demonstrated skills to successfully perform the assigned duties and responsibilities; and/or equivalent experience/training.

Preferred Qualifications:

  • Experience applying the following regulations and guidelines:
  • Good Clinical Practice Guidelines
  • Health Information and Accountability Act (HIPAA)
  • The Protection of Human Research Subjects
  • CHR regulations for recruitment and consent of research subjects
  • Effective Cash Handling Procedures
  • Environmental Health and Safety Training 
  • Fire Safety Training

of time

Essential Function (Yes/No)

  

Key Responsibilities

(To be completed by Supervisor)

50

YesStudy Coordination and Data Collection
  • Identify subjects, develop recruitment and retention strategies, and screen and enroll study subjects.
  • Schedule subjects for study visits; meet with them to administer questionnaires, collect medical history and perform study procedures.
  • Maintain rapport and relationships with subjects to ensure effective communication and retention; respond to their diverse needs, schedule follow-up appointments, and become their intermediary; discuss study outcomes with providers to ensure continuity of care.
  • Obtain informed consent; review information with subjects; assess and advocate for patient safety throughout each protocol procedure.
  • Oversee subject reimbursement; work to resolve discrepancies and issues.         
  • Work with staff to ensure procedures are completed, specimens properly stored, and required data collected at visits; and ensure correct shipping and labeling measures.
  • Coordinate, communicate and network with other studies and technicians to ensure scheduling efficiency; communicate with any affiliated groups.
  • Conduct reviews of medical charts and electronic records to extract medical information and other data for use in studies.
  • Implement needs assessments and recommendations for enhancements on patient coordination, data collection, data management, protocol adherence and study collaboration.
  • Attend and actively participate in regular team meetings

20

YesData management and reporting of results
  • Collect data during subject visits; enter data from visits, procedures, lab tests, and other subject-related participation into databases in a timely manner.
  • Manage database structure for each protocol; update databases to improve data analysis and management; create new databases as needed.
  • Create and maintain comprehensive data sets as requested by the CRC Supervisor and/or PI.  
  • Maintain data collection forms for effective data collection, entry, and analysis.  
  • Perform queries and analysis in databases.
  • Work with Supervisor to maintain complete and accurate data in the study database; analyze the data as they become available.

5

 

Quality control procedures 

  • Oversee data integrity; initiate assessments of the adequacy of existing policies and procedures on subject recruitment, data collection, and data management.  
  • Update and maintain a procedure manual documenting all study-related procedures; help develop a plan to ensure consistency in data collection and data entry.
  • Implement and maintain periodic quality control procedures
  • Suggest modifications to the administrative infrastructure to accommodate increasing complexity of studies.  
  • Modify data collection instruments
  • Maintain subject tracking systems.
  • Arrange the exchange of and transport of specimens with collaborating Investigators and staff.
  • Some specimen processing such as centrifugation, aliquoting, and shipping may be required in some studies
  • Oversee the incoming data interpreted from samples and ensure that it is utilized correctly for analysis and publications.
  • Ensure integrity and security of samples.
  • If the incumbent is a certified phlebotomist, perform phlebotomy as needed. 

5

 Study Implementation

5

 Specimen Management/ Maintenance

10

 

Protocol Submissions and Adherence

  • Enter all existing and new study protocols into the Committee on Human Research (CHR) online system; seek assistance on maintaining all protocols in the system by communicating with CHR Analysts.
  • Design and enhance case report forms and data collection forms as needed; provide manuscript feedback; continue to develop and maintain systems for assuring protocol adherence and data quality.
  • Participate in the review and writing of protocols and related procedures to ensure institutional review board approval within University compliance.
  • Renew, modify, and submit CHR applications and protocols; ensure that protocol applications are submitted in a timely manner; serve as a liaison between CHR and study Investigators.
  • Provide quality assurance checks to note if protocols or UCSF CHR applications need to be modified; evaluate protocols on an ongoing basis and implement improvements as needed.

5

 Regulatory responsibilities
  • Assure studies are carried out according to Code of Federal Regulations, Good Clinical Practice, and UCSF regulations.
  • Initiate and follow-up on CHR submissions and modifications; track approval status.
  • Interface with departments to obtain UCSF approval prior to study initiation.
  • Maintain regulatory documents; monitor timelines for data submission; document adverse events and submit to appropriate departments.
  • Use sound judgment to maintain patient confidentiality when communicating with agencies, healthcare providers, other studies, and outside departments.
  • Participate in and cooperate with any internal and external audits or reviews of study protocols; prepare necessary documentation.

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