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Text Annotation Jobs in Florida (NOW HIRING)

Data Scientist Lead

Tampa, FL · On-site

$140 - $200/hr

Build and fine‑tune multimodal document understanding and text categorization models. Leverage ... Establish best practices for annotation quality management, training data curation, active learning ...

Build and fine-tune multimodal document understanding and text categorization models. Leverage the ... Establish best practices for annotation quality management, training data curation, active learning ...

Build and fine-tune multimodal document understanding and text categorization models. Leverage the ... Establish best practices for annotation quality management, training data curation, active learning ...

Build and fine-tune multimodal document understanding and text categorization models. Leverage the ... Establish best practices for annotation quality management, training data curation, active learning ...

Data Scientist Lead

Tampa, FL · On-site

$170 - $230/hr

Build and fine‑tune multimodal document understanding and text categorization models. Leverage ... Establish best practices for annotation quality management, training data curation, active learning ...

Showing results 21-40

Text Annotation information

What is a text annotation?

A Text Annotation job involves labeling and categorizing text data to help train machine learning models. Annotators add tags, metadata, or classifications to text, enabling AI systems to understand language patterns. This work is essential for applications like chatbots, search engines, and sentiment analysis. Strong attention to detail and language proficiency are key skills for this role.

What are the typical day-to-day responsibilities for someone working in text annotation?

Text Annotation professionals spend much of their day reading and labeling text data according to specific guidelines, ensuring that information is correctly categorized and flagged. This can involve highlighting entities, identifying sentiments, tagging parts of speech, or annotating complex relationships within text documents. They frequently collaborate with project managers, data scientists, and quality assurance teams to clarify instructions and maintain data consistency. The role often involves independent work, but regular check-ins and feedback sessions help maintain accuracy and enhance understanding of evolving annotation requirements. This combination of independent and collaborative tasks makes the position dynamic and integral to successful AI or NLP project outcomes.

What are the key skills and qualifications needed to thrive in text annotation, and why are they important?

Strong language proficiency, attention to detail, and critical thinking are essential skills for succeeding as a Text Annotation specialist, often supported by a bachelor's degree in linguistics, computer science, or a related field. Familiarity with annotation tools like Labelbox, Prodigy, or the Amazon Mechanical Turk platform, as well as knowledge of data privacy and handling protocols, is typically required. Excellent communication, self-motivation, and the ability to focus on repetitive tasks help individuals excel in this position. These capabilities ensure high-quality, consistent data labeling for machine learning models, supporting the development of cutting-edge AI solutions.

What are the most commonly searched types of Text Annotation jobs in Florida?

The most popular types of Text Annotation jobs in Florida are:

What cities in Florida are hiring for Text Annotation jobs?

Cities in Florida with the most Text Annotation job openings:

Infographic showing various Text Annotation job openings in Florida as of August 2026, with employment types broken down into 3% Internship, 57% Full Time, 26% Part Time, 3% Temporary, and 11% Contract. Highlights an 77% In-person, 3% Hybrid, and 20% Remote job distribution.

$140 - $200/hr

Other

Medical, Retirement

Posted 18 days ago


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.
  • 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. You will drive Data Science projects, leveraging expertise to deliver innovative solutions for the Healthcare Provider team.

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