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Hourly Remote Data Labeling Jobs in Tennessee (NOW HIRING)

DataAnnotation

Data Science Consultant

Nashville, TN · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... Competitive pay: projects are paid hourly, starting at $40+ USD per hour. Impact: help shape the ...

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Hourly Remote Data Labeling information

What are the key skills and qualifications needed to thrive as an Hourly Remote Data Labeler, and why are they important?

To thrive as an Hourly Remote Data Labeler, you need strong attention to detail, basic computer literacy, and the ability to follow specific guidelines, often with a high school diploma or equivalent. Familiarity with data annotation tools and platforms such as Labelbox, Prodigy, or internal company systems is typically required. Reliability, time management, and effective written communication are crucial soft skills for meeting deadlines and maintaining quality in a remote setting. These skills and qualities are important to ensure accurate, consistent data labeling that directly impacts the performance of AI and machine learning models.

What are some common challenges faced by hourly remote data labeling professionals, and how can they be managed?

Hourly remote data labeling professionals often encounter challenges such as maintaining consistent accuracy, managing repetitive tasks, and staying self-motivated while working independently. To manage these challenges, it's important to set up a dedicated workspace, take regular breaks to reduce fatigue, and follow established labeling guidelines closely. Frequent communication with team leads and participating in quality feedback sessions can also help ensure your work meets project standards and fosters professional growth.

What is hourly remote data labeling?

Hourly remote data labeling is a job where individuals work from home to tag, categorize, or annotate data (such as images, videos, text, or audio) for machine learning and artificial intelligence projects. Workers are typically paid by the hour and use online platforms to complete labeling tasks assigned by companies or research organizations. This work is crucial because AI models need large volumes of accurately labeled data to learn and function properly. The job usually requires attention to detail and may involve following specific guidelines to ensure data quality.

What is the difference between Hourly Remote Data Labeling vs Data Annotation Specialist?

AspectHourly Remote Data LabelingData Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with some industry-specific knowledge
Work EnvironmentRemote, flexible hoursRemote, often project-based or ongoing
Industry UsageCommon in AI/ML developmentUsed across tech, healthcare, automotive sectors
Search IntentLooking for remote data labeling jobsSearching for data annotation roles

Both roles involve labeling or annotating data for machine learning models, often remotely. The main difference lies in terminology and specific industry usage, but they share similar credentials and work environments.

What are popular job titles related to Hourly Remote Data Labeling jobs in Tennessee? For Hourly Remote Data Labeling jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Data Labeling jobs in Tennessee look for? The top searched job categories for Hourly Remote Data Labeling jobs in Tennessee are:
What cities in Tennessee are hiring for Hourly Remote Data Labeling jobs? Cities in Tennessee with the most Hourly Remote Data Labeling job openings:
Hourly Remote Data Labeling jobs near you
Remote Data Science Consultant & AI Trainer

Remote Data Science Consultant & AI Trainer

DataAnnotation

Nashville, TN • On-site, Remote

$60/hr

Full-time

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

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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