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Data Labeler Remote Jobs in Florida (NOW HIRING)

Truvani

Direct Response Copywriter - REMOTE

Tampa, FL · On-site +1

$75K - $105K/yr

... labels without lies. Founded on one simple belief - that the ingredients in your food and ... Test and iterate. Use performance data (CTR, hook rate, CPA) and customer feedback to refine ...

Truvani

Direct Response Copywriter - REMOTE

Tampa, FL · Remote

$75K - $105K/yr

... labels without lies. Founded on one simple belief - that the ingredients in your food and ... Test and iterate. Use performance data (CTR, hook rate, CPA) and customer feedback to refine ...

Zapp

US Buying & Operations Manager

Miami, FL · Remote

$80K - $120K/yr

NYC, SF, LA, CHI or MIA - Full-time (remote) We are looking for a hands-on US Buying & Operations ... Use demand data and sales trends to forecast, plan buys and manage inventory, minimising both ...

PNC Bank

Head of Sales, Linga

Naples, FL · On-site +1

... white-label partners), and expansion of the existing customer base. Reporting directly to the ... Use data-driven insights to continuously optimize performance across all channels. Maintain ...

Intermountain Health

$31.01 - $48.84/hr

Analyzes data, develops reports, reviews trends and recommend enhancements as defined by the ... Physical Requirements Ongoing need for employee to see and read information, labels, documents ...

Imh

Revenue Integrity Analyst II

Lake Park, FL · On-site +1

$37.87 - $59.63/hr

Analyzes data, develops reports, reviews trends and recommends enhancements as defined by the ... Ongoing need for employee to see and read information, labels, documents, monitors, identify ...

ASCENSUS

NQ Plan Analyst

Tampa, FL · Remote

The NQ Plan Analyst team (Direct and Private Label) oversees the day-to-day workflow for assigned ... Research data issues, including information on Risk Mitigation reports, to ensure data completeness.

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Data Labeler Remote information

Is data labelling a good career?

Data labeling is an entry-level role that involves annotating data for machine learning models, often requiring attention to detail and basic technical skills. It can provide a stepping stone into the tech industry, but it typically offers limited advancement opportunities and lower pay compared to more specialized roles. Many professionals use it as initial experience before moving into data science or related fields.

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

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

How can I make 2000 a week working from home?

A remote data labeler can potentially earn around $2000 per week by working full-time hours, often 40 hours or more, and gaining experience or specializing in high-demand data annotation tasks. Increasing earnings may involve working for multiple clients, improving skills with annotation tools, or taking on higher-paying projects, but consistent high weekly income depends on workload, rates, and efficiency.

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

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

How much are data labelers paid?

Data labelers working remotely typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer project-based pay or bonuses for accuracy and efficiency.

Is data labeling work from home?

Data labelers often work remotely, as the job typically involves reviewing and annotating data using a computer and internet connection. Many companies offer remote data labeling positions with flexible schedules, requiring basic computer skills and attention to detail.
What are the most commonly searched types of Data Labeler jobs in Florida? The most popular types of Data Labeler jobs in Florida are:
What are popular job titles related to Data Labeler Remote jobs in Florida? For Data Labeler Remote jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Labeler Remote jobs in Florida look for? The top searched job categories for Data Labeler Remote jobs in Florida are:
What cities in Florida are hiring for Data Labeler Remote jobs? Cities in Florida with the most Data Labeler Remote job openings:
Data Labeler Remote jobs near you
Infographic showing various Data Labeler Remote job openings in Florida as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 12% Part Time, and 7% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Applied Data Scientist

Professional Staffing Services

Orlando, FL • Remote

Contractor

Posted 14 days ago

Job description

Applied Data Scientist - Contract to Hire

Location: Florida (Remote but will need to travel to Orlando for your first day, and for occasional meetings and trainings. )

Employment Type: Full-Time, Pay: ~ 100K-150K

Sponsorship: Not Available (Now or in the future)

About The Company

Our client drives innovative, datadriven insights and scalable AI solutions across the entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform audience data into actionable strategies and operational products.

A successful Applied Data Scientist thrives on both analytical creativity and production rigor. As a key member of our client's team, you will own endtoend modeling and deployment work-from the conceptual framing of business problems to data ingestion, model development, and reliable production delivery. Your work will directly shape how our company delivers value to clients and internal stakeholders.

Position Summary & Location Requirements

This is a Florida-based role. While the day-to-day work offers remote flexibility, candidates must reside in the state of Florida and meet the following travel requirements:

  • Day One: Ability to travel to Orlando, FL for your first day/onboarding.
  • Ongoing: Ability to travel to Orlando on occasion for collaborative meetings, trainings, and to support business needs.

Key Responsibilities

In this role, you will bridge the gap between business strategy and technical execution. Specifically, you will:

  • Model & Solution Development: Translate ambiguous business questions into structured analytical and ML solutions. Develop, validate, and optimize models impacting forecasting, segmentation, personalization, recommendation, or operational efficiency.
  • Production & MLOps: Build productionready pipelines and deploy models into scalable environments using robust MLOps practices (CI/CD, automated testing, monitoring), ensuring long-term lifecycle maintenance.
  • Collaboration & Communication: Partner cross-functionally to bridge business requirements and technical design. Communicate insights and technical decisions clearly to both technical and nontechnical stakeholders.
  • Documentation & Standards: Document all models, pipelines, and deployment processes comprehensively to ensure maintainability, reproducibility, and knowledge sharing.
  • Innovation: Stay ahead of emerging tools, techniques, and frameworks in ML/AI to influence best practices across the organization.

Core Qualifications

  • Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Professional Experience: 5+ years of industry experience (excluding internships) in data science and machine learning, including proven ownership of model productization, monitoring, and iterative improvement.
  • Core ML Experience: 3+ years of building machine learning models for business applications (outside of academia), with deep expertise in both supervised and unsupervised learning algorithms.
  • Technical Stack:
  • Python: Strong programming skills with hands-on experience building, training, deploying, and monitoring ML models.
  • SQL: 2+ years of experience with database querying, data preparation, and analysis.
  • Data Warehousing: Working knowledge of large-scale platforms (e.g., Snowflake, SQL Server, BigQuery, Redshift).
  • Cloud Platforms: Familiarity with cloud environments (AWS, Azure, or GCP) and designing end-to-end ML pipelines from ingestion to production serving.
  • Execution Skills: Outstanding analytical skills to diagnose and resolve complex system issues, with a proven ability to manage multiple projects and prioritize tasks effectively.

What Sets You Apart (Preferred Qualifications)

  • Advanced Degree: Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Domain Expertise: Industry experience in entertainment or e-commerce, including domains such as theme parks, hospitality, live performances, ticketing, or retail marketplaces.
  • Advanced ML Architectures: Hands-on experience designing and deploying recommendation models (collaborative filtering, content-based, transformer-based) or working with data labeling, taxonomy design, and classification frameworks.
  • Generative AI: Familiarity with GenAI techniques, language modeling, or frameworks like AWS Bedrock and Hugging Face.
  • Deep MLOps Tooling: Advanced experience with tools like SageMaker, Lambda, Airflow, or MLflow, and the ability to guide architectural/strategic decisions for ML infrastructure.

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