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Remote Data Labeling Analyst Jobs in California (NOW HIRING)

Remote Role Responsibilities * Review and evaluate AI-generated outputs related to threat analysis ... Annotate, label, and validate data across cybersecurity use cases like CVE classification accuracy ...

Senior Data Analyst

Los Angeles, CA · Remote

$109K - $171K/yr

Remote US & Canada We are seeking a highly motivated and autonomous Senior Data Analyst to join our team. In this role, you will be pivotal in surfacing insights and providing guidance to a broad ...

Sr. Data Analyst

San Francisco, CA · Remote

$90K - $130K/yr

In this role, you'll not only analyze data to generate insights but also help connect and organize ... Global remote flexibility - The opportunity to directly influence the future of no-code and AI ...

Sr. Data Analyst

San Francisco, CA · On-site +1

$90K - $130K/yr

In this role, you'll not only analyze data to generate insights but also help connect and organize ... Global remote flexibility - The opportunity to directly influence the future of no-code and AI ...

Remote Pay Range: $60 - $65/hr on W2 Job Summary: We are seeking a Data Analysis Lead to join our team in a remote role, supporting our sales planning and execution from the United States, preferably ...

Remote Who is IDEX Health & Science (IH&S)? As a business unit of IDEX Corporation, IH&S has a long ... Analyze financial and operational data to identify ways to capture and report on trends, variances ...

Showing results 41-60

Remote Data Labeling Analyst information

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

To thrive as a Remote Data Labeling Analyst, you need strong attention to detail, analytical thinking, and basic data management skills, typically supported by a high school diploma or higher. Familiarity with annotation tools, data labeling platforms, and sometimes basic programming or spreadsheet software is required. Strong communication, time management, and the ability to work independently are crucial soft skills for excelling remotely. These abilities ensure high-quality, accurate data labeling that directly impacts the effectiveness of AI and machine learning systems.

What are some common challenges faced by remote data labeling analysts, and how can they be addressed?

Remote Data Labeling Analysts often encounter challenges such as maintaining focus during repetitive tasks, managing time effectively across multiple projects, and ensuring high accuracy in labeling complex data sets. To address these challenges, it is helpful to follow structured workflows, take regular breaks to reduce fatigue, and leverage collaboration tools to communicate with team members for clarification or feedback. Staying updated with labeling guidelines and participating in regular training sessions can also help improve both productivity and quality of work.

What does a remote data labeling analyst do?

A Remote Data Labeling Analyst is responsible for reviewing, tagging, and annotating data—such as images, videos, text, or audio—to help train machine learning models. Working remotely, they use specialized software to classify or categorize this data according to specific guidelines. Their work is crucial for improving the accuracy and performance of artificial intelligence systems, as well-labeled data enables the AI to learn and make better predictions. This role typically requires attention to detail, consistency, and the ability to follow complex instructions.

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

AspectRemote Data Labeling AnalystRemote Data Annotator
CredentialsBasic data labeling skills, familiarity with annotation toolsSimilar credentials, often entry-level
Work EnvironmentRemote, often part of a data teamRemote, typically individual tasks
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI training data preparation
Job FocusLabeling and categorizing data for machine learningAnnotating data with labels or tags

The Remote Data Labeling Analyst and Remote Data Annotator roles are similar, both involving data labeling tasks in a remote setting. The Analyst may have additional responsibilities like quality checks or data management, but both positions 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 California? The most popular types of Data Labeling Analyst jobs in California are:
What are popular job titles related to Remote Data Labeling Analyst jobs in California? For Remote Data Labeling Analyst jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Data Labeling Analyst jobs in California look for? The top searched job categories for Remote Data Labeling Analyst jobs in California are:
What cities in California are hiring for Remote Data Labeling Analyst jobs? Cities in California with the most Remote Data Labeling Analyst job openings:
Infographic showing various Remote Data Labeling Analyst job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Analyst (with Preparation Material)

Kite Ping

Berkeley, CA • Remote

Full-time

Re-posted 3 days ago


Job description

Company Description

Kite Ping is a professional network where people can give or get career suggestions. Its a start up in Silicon Valley.


Job Description


dataanalyst.xyz 

This prep material covers most of our requirements. Candidates can prepare here.

This is a remote position and we are hiring data analysts to help us analyze our business analytics and performance metrics data. The requirements are fairly straightforward and are described below.

Qualifications

Responsibilities:

Conduct data analysis in support of applications and projects, including identifying and documenting business rules, data needs and data specifications.

Collaborate with development and business teams to drive data informed decision making.

Participate in design, and development of the product.

Qualifications & Skills:

Bachelor's Degree - any quantitative or technical field.

Proficiency in MS Excel and SQL tools.

Strong Understanding of Fundamental Statistics & Web Analytics.

Excellent communication skills in both oral and written forms.

Display a sense of curiosity, enthusiasm and eagerness to understand business constraints, environment and impact on regulation for the financial industry.

Excellent organization, analytical and time management skills.

Strong problem solving/troubleshooting skills.

Ability to work independently and become an effective team member.


Additional Information

All your information will be kept confidential according to EEO guidelines.