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Data Labelling Jobs in Kissimmee, FL (NOW HIRING)

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Data Labelling information

See Kissimmee, FL salary details

$40.6K

$145.8K

$215.2K

How much do data labelling jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data labelling in Kissimmee, FL is $145,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $150,200.00 per year, depending on experience, location, and employer.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.

What job categories do people searching Data Labelling jobs in Kissimmee, FL look for?

The top searched job categories for Data Labelling jobs in Kissimmee, FL are:

What cities near Kissimmee, FL are hiring for Data Labelling jobs?

Cities near Kissimmee, FL with the most Data Labelling job openings:

Infographic showing various Data Labelling job openings in Kissimmee, FL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $145,811 per year, or $70.1 per hour.

Applied Data Scientist

Professional Staffing Services Group

Orlando, FL • On-site

$140K - $185K/yr

Full-time

Re-posted 21 days ago


Job description

Applied Data Scientist - Contract to HireLocation: Florida (Remote but will need to travel to Orlando for your first day, and for occasional meetings and trainings. )***Also considering candidates in TX, GA, and NC. Must be willing to travel.Employment Type: Full-Time, Pay: ~ 140K - 185KSponsorship: Not Available (Now or in the future)About The CompanyOur client drives innovative, data‑driven 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 end‑to‑end 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 RequirementsThis is a Florida-based role. While the day-to-day work offers remote flexibility, candidates must reside in the state of Florida or reside in GA, TX, and NC and meet the following travel requirements:Day One: Ability to travel to Orlando, FL or the closest office local to your area for your first day/onboarding.Ongoing: Ability to travel to Orlando or closest office local to your area on occasion for collaborative meetings, trainings, and to support business needs.Key ResponsibilitiesIn 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 production‑ready 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 non‑technical 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 QualificationsEducation: 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.