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Data Annotation Jobs in Brandon, FL (NOW HIRING)

JP Morgan Chase

Data Scientist Lead

Tampa, FL · On-site

Establish best practices for annotation quality management, training data curation, active learning strategies, and ground truth validation to ensure high-quality labeled datasets. * Design, manage ...

JPMorgan Chase & Co

Data Scientist Lead

Tampa, FL · On-site

Establish best practices for annotation quality management, training data curation, active learning strategies, and ground truth validation to ensure high-quality labeled datasets. * Design, manage ...

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Data Annotation information

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$8

$22

$48

How much do data annotation jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for data annotation in Brandon, FL is $22.70, according to ZipRecruiter salary data. Most workers in this role earn between $15.35 and $27.03 per hour, depending on experience, location, and employer.

Is data annotation a legitimate?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It is commonly performed remotely and requires attention to detail, basic technical skills, and familiarity with annotation tools. Many companies hire data annotators as part of their AI development teams.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.

Do people actually make money on data annotation?

Data annotation jobs can provide a source of income, with pay rates varying based on the complexity of tasks, platform, and experience. Many annotators earn hourly or per-task wages, but earnings often depend on the volume of work completed and the employer's pay structure.

Is it hard to get hired for data annotation?

Getting hired for a data annotation role generally depends on the employer's requirements, such as attention to detail and basic computer skills. Many positions are entry-level and may not require prior experience or certifications, making them accessible to a wide range of applicants. However, competition can vary based on the number of available jobs and the quality of applicants.
What cities near Brandon, FL are hiring for Data Annotation jobs? Cities near Brandon, FL with the most Data Annotation job openings:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Brandon, FL as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, and 12% Part Time. Highlights an 45% Physical, 1% Hybrid, and 54% Remote job distribution, with an average salary of $47,215 per year, or $22.7 per hour.
Data Scientist Lead

Data Scientist Lead

JP Morgan Chase

Tampa, FL • On-site

Full-time

Medical, Retirement

Posted 10 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 469 frontline employees who took The Breakroom Quiz

46th of 141 rated banks

Job description

As Data Scientist Lead within Commercial & Investment Bank with the Healthcare Provider team, you will lead a team in building advanced solutions for image classification, text categorization, and intelligent data extraction from scanned documents. You will have deep proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, AWS SageMaker/Bedrock, and hands-on experience with CNN/transformer architectures, OCR technologies, and multimodal document understanding models. This role involves managing the full ML lifecycle, from prototyping to production deployment on AWS EKS.

Job responsibilities 

  • Lead and mentor a team of data scientists in designing and executing advanced analytics and modeling projects focused on image classification, text categorization, and intelligent data extraction from scanned document images. Foster a culture of curiosity, analytical rigor, and continuous learning by developing team members in deep learning, computer vision, NLP, and document AI techniques.
  • Define and drive the analytical strategy for document understanding use cases, identifying the optimal combination of computer vision, NLP, and multimodal approaches.
  • Build and fine-tune multimodal document understanding and text categorization models. Leverage the interplay of textual content, spatial layout, and visual features to extract structured fields and key-value pairs from complex scanned documents, while enabling automated categorization, routing, metadata tagging, and entity extraction.
  • Design rigorous experimentation and data quality frameworks, including A/B testing, cross-validation strategies, and statistical significance testing to evaluate model performance and hyperparameter tuning. Establish best practices for annotation quality management, training data curation, active learning strategies, and ground truth validation to ensure high-quality labeled datasets.
  • Design, manage, and optimize the workflows involved in preparing data for machine learning model training, select statistical or Deep Learning models that are best positioned to achieve business results.
  • Develop and deploy models using Python and AWS SageMaker, managing the full lifecycle from exploratory data analysis and prototyping through production deployment, monitoring, and performance tracking. Collaborate with data engineers and ML engineers to ensure seamless integration of analytical models into production document processing pipelines and data workflows.


Required qualifications, capabilities, and skills 

  • Bachelor's degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
  • 7+ years of experience in data science or quantitative analytics, with at least 2+ years of experience in document AI, computer vision, or NLP domains.
  • Strong foundation in statistics, mathematics, and programming, including probability, mathematical modeling, and experimental design with the ability to rigorously evaluate model performance with advanced proficiency in Python for data analysis, modeling, and visualization, and deep experience in PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, OpenCV, pandas, NumPy, matplotlib, and seaborn.
  • Hands-on experience with CNN and transformer architectures for document AI for image classification, transfer learning, and feature extraction; multimodal document understanding combining textual, visual, and layout features; and NLP models for text categorization, sequence labeling, named entity recognition, and semantic analysis with familiarity with additional computer vision models including object detection, image segmentation, and Vision Transformers.
  • Working experience with OCR technologies and image preprocessing, for text extraction from scanned documents, with an understanding of OCR accuracy metrics, preprocessing optimization, and error analysis. Proficiency in image preprocessing techniques for scanned documents in TIF/PNG format, including deskewing, binarization, resolution enhancement, noise removal, and multi-page document handling.
  • Hands-on experience with AWS SageMaker and Amazon Bedrock, including building, training, tuning, and deploying ML models in cloud-based production environments (notebook instances, training jobs, inference endpoints), as well as exploring foundation models and generative AI capabilities to augment document understanding and classification workflows and experience with containerized deployments on AWS EKS for productionizing data science models and analytical services at scale.
  • Proficiency in SQL with strong working knowledge of Oracle databases for complex data extraction, transformation, and analysis of document metadata and extracted content with working knowledge of Java and Groovy for collaborating with engineering teams and understanding enterprise application codebases and strong understanding of annotation tools, active learning strategies, and training data management for supervised learning in document AI use cases.

Preferred qualifications, capabilities, and skills 

  • Domain expertise in the healthcare industry 

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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