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Freelance Data Labeling Analyst Jobs in Utah (NOW HIRING)

... data labeling operations. Responsibilities : • Conduct ongoing performance management: create coaching plans, track progress, conduct monthly 1:1's, and complete monthly analyst reports • ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

... labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping and gap analysis across structured, unstructured, cloud, and on ...

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Freelance Data Labeling Analyst information

What is a freelance data labeling analyst?

A Freelance Data Labeling Analyst is a professional who works independently to tag, categorize, or annotate data—such as images, texts, or audio—to help train machine learning models. These analysts play a crucial role in ensuring that artificial intelligence systems receive accurate and high-quality training data. Their work typically involves reviewing raw data and applying specific labels according to established guidelines. Freelance analysts can work remotely for various clients, often via online platforms or data annotation companies. This job requires attention to detail, consistency, and sometimes domain-specific knowledge.

What are the key skills and qualifications needed to thrive as a freelance data labeling analyst?

To thrive as a Freelance Data Labeling Analyst, you need strong attention to detail, data literacy, and a solid understanding of data annotation standards, often supported by a background in computer science or related fields. Familiarity with data labeling platforms, annotation tools like Labelbox or Supervisely, and sometimes knowledge of Python or SQL is valuable. Diligence, self-motivation, and the ability to follow complex guidelines set apart top analysts in this role. These skills ensure accurate, high-quality labeled datasets that are crucial for effective machine learning model training.

What are some common challenges freelance data labeling analysts face when working with multiple clients?

Freelance Data Labeling Analysts often juggle varied guidelines, annotation tools, and project requirements from different clients. Adapting quickly to new labeling standards and software platforms is essential, as each client may have their own specifications for data quality and turnaround times. Additionally, managing communication across multiple teams and ensuring consistent delivery can require strong organizational skills and proactive time management. Building a transparent workflow and clarifying expectations with each client helps mitigate these challenges.

What is the difference between Freelance Data Labeling Analyst vs Data Annotator?

AspectFreelance Data Labeling AnalystData Annotator
CredentialsBasic data labeling skills, sometimes certifications in data annotation toolsSimilar; often no formal certifications required
Work EnvironmentRemote, freelance projects for various clientsRemote or in-house, depending on employer
Industry UsageUsed across AI, machine learning, and data science projectsPrimarily in AI training datasets and machine learning
Search & Comparison IntentHigh overlap; both involve labeling data for AI models

Both Freelance Data Labeling Analysts and Data Annotators perform data labeling tasks essential for training AI models. The main difference lies in the freelance nature and potential project variety for Analysts, while Annotators may work more consistently within specific companies or platforms. Both roles require similar skills and are used widely in AI and machine learning industries.

What are the most commonly searched types of Data Labeling Analyst jobs in Utah?

The most popular types of Data Labeling Analyst jobs in Utah are:

What are popular job titles related to Freelance Data Labeling Analyst jobs in Utah?

For Freelance Data Labeling Analyst jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Freelance Data Labeling Analyst jobs in Utah look for?

The top searched job categories for Freelance Data Labeling Analyst jobs in Utah are:

What cities in Utah are hiring for Freelance Data Labeling Analyst jobs?

Cities in Utah with the most Freelance Data Labeling Analyst job openings:

Data Labeler Manager

Tesla

Draper, UT • On-site

Full-time

Re-posted 7 days ago


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Job description

Job Summary:
Tesla is a leading company in the electric vehicle and AI space, seeking a Data Labeler Manager to oversee a team responsible for annotating data for their AI software. The role involves managing performance, ensuring data integrity, and collaborating with engineering teams to enhance the efficiency of data labeling operations.
Responsibilities:
• Conduct ongoing performance management: create coaching plans, track progress, conduct monthly 1:1’s, and complete monthly analyst reports
• Evaluate daily performance in proprietary software to report daily summaries and team metrics to ensure the team is consistently exceeding expectations
• Work directly with engineers and Tesla AI leadership and own annotation policies that require an understanding of both technical and operational constraints
• Have a solid understanding of project guidelines to be able to communicate labeling concepts effectively, labeling inefficiencies, assist in creating documentation and training materials
• Execute proper headcount allocation between quality control, labeling, and prioritize job queues daily as directed by leadership
• Ensure documentation and daily planning for the team is accurate and consistently updated
• Ensure team alignment with company policies
• Other supervisory duties such as employee development, conducting bi-yearly performance reviews and monthly performance check-ins with Team Leads and Data Labelers, and accurately manage timekeeping
Qualifications:
Required:
• Experience managing and motivating medium-sized teams that perform manual operations
• Ability to manage time efficiently, prioritizing tasks by order of precedence and completing in a timely manner
• Proven record of accomplishments executing and meeting sensitive deadlines with experience managing multiple competing projects with limited resources
• Strong problem-solving skills, with an aptitude for quickly learning systems with minimal training and can adapt in an ambiguous environment
• Effective communication and presentation skills - can explain complicated topics and ideas in a clear and concise manner
• Commitment to data accuracy and throughput
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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