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Remote Data Labeling Analyst Jobs in Illinois (NOW HIRING)

Data Entry Specialist / Data Analyst

Chicago, IL · Remote

$17.50 - $23.50/hr

About the job Data Entry Specialist / Data Analyst We are Legitimate Work From Home Data Entry Jobs ... Our paid focus group members come from all backgrounds and industries including remote data entry ...

Remote * Commitment : 10-40 hours/week What You'll Do * Analyze vulnerability reports, CVEs, and ... Generate, label, and validate realistic security-reasoning data used to train and benchmark AI ...

Remote Data Engineer

Oak Brook, IL · Remote

$115.70K - $138.90K/yr

Build and maintain real-time and batch data pipelines across the advanced analytics platform. * Design, develop and orchestrate highly robust and scalable ETL pipelines. * Design and implement ...

Data Entry Clerk I

Chicago, IL · Remote

$17.50 - $23.50/hr

We are seeking a detail-oriented and highly organized Remote Data Entry Clerk to join our team. In ... analysis Assist in generating reports and summaries as needed Communicate with team members to ...

Data Analyst

Chicago, IL · On-site +1

$39.43 - $44.43/hr

... labelling standards and other source system information to produce IT consumable information Data ... Remote VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity ...

Remote * Commitment : 10-40 hours/week What You'll Do * Analyze realistic data security and DLP ... Generate, label, and validate data-security cases used to train and benchmark AI systems * Help AI ...

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Remote Data Labeling Analyst information

What are the key skills and qualifications needed to thrive as a Remote Data Labeling Analyst, and why are they important?

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 Illinois? The most popular types of Data Labeling Analyst jobs in Illinois are:
What job categories do people searching Remote Data Labeling Analyst jobs in Illinois look for? The top searched job categories for Remote Data Labeling Analyst jobs in Illinois are:
What cities in Illinois are hiring for Remote Data Labeling Analyst jobs? Cities in Illinois with the most Remote Data Labeling Analyst job openings:

Remote Data Analyst - Entry Level

Easy Recruiter

Chicago, IL • On-site, Remote

Other

This job post has expired today. Applications are no longer accepted.


Job description

Remote Data Analyst - Entry Level

We entertain millions of people across the globe with the most amazing and immersive interactive software in the industry. But making games is hard. That's why we employ the most creative, passionate people in the industry. The Workplaces team oversees workplace environments and the related employee experience globally and supports and maintains spaces that are vibrant, fresh, branded, and inspiring. The team also provides relevant programs that differentiate us as an employer of choice and support EA's ability to attract and retain the talent needed to power our Company. Workplace Experience is focused on services and programs that directly impact employee effectiveness, provide a healthy physical office environment, create a consistent physical setting and workplace experience globally while reflecting local culture, build community and connectedness among our people, directly help foster our values, and apply best practices in environment design.

Workplace Experience is going through an exciting time as we redefine the future of EA's workforce and implement our new ways of working. As a Data Analyst you will focus on discovering trends, identifying risks and constraints, providing recommendations, being an advisor to the WE senior leadership team. You will apply your modeling skills to develop forecasts and insights to improve existing workplaces to create an amazing employee experience as we evolve our future workplace model. You will wrangle data across multiple data sources, apply the right models, and visualize insights for senior leaders and partners. You'll also learn new systems, tools, and bring industry best practices to analyze big data and enhance our workplace analytics. You will report to the Senior Manager for the Workplace Experience Program Management Office. Key responsibilities include communicating complex analysis and concepts and providing readable dashboards to surface relevant insights with clear narratives to senior leadership and non-technical partners, developing forecasting models to understand EA's future ways of working and the evolution of our workforce, working with program managers and leadership to determine business problems and use statistical analysis, simulations, predictive modeling, or other methods to analyze and develop practical solutions, advocating for the importance of data-driven decision-making and building relationships with partners who rely on people data to ensure understanding on needs, definition of metrics and ways of working, championing for data quality, creating policy and implementing monitoring solutions to ensure compliance, performing research, assembling and integrating data from multiple sources, conducting analyses, designing and implementing analytical solutions, identifying and advocating for technical options related to machine learning, data mining, and other statistical approaches, and maintaining data repositories, interfaces and protocols.

What we're looking for includes a minimum of bachelor's Degree in Data Science, Applied Mathematics, Architecture or Engineering with an emphasis on quantitative methods, 3+ years in a past data analyst role (or similar) that involved thinking of big pictures, suggesting changes to process, identifying risks and potential opportunities for data improvement, communicating with non-technical partners, expert SQL including experience querying complex data sets, data analysis- spreadsheet mastery including VBA, PivotTables, and array functions - or similar tools used for discovering data patterns and correlations through statistical methods, managing and facilitating collaborations with global partners, customer-centric skills - able to engage with business and IT partners to discover requirements for Business Intelligence solutions, storytelling and project management skills - direct experience with data visualization tools such as Power BI or Tableau, understanding of network and data privacy requirements with knowledge of integrity and security tools, experience with Workday, Visier, CCure, and FMI a plus, and experience working with human capital data.