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Data Annotation Services Jobs in Florida (NOW HIRING)

JP Morgan Chase

Data Scientist Lead

Tampa, FL

Establish best practices for annotation quality management, training data curation, active learning ... services at scale. * Proficiency in SQL with strong working knowledge of Oracle databases for ...

JPMorgan Chase & Co.

Data Scientist Lead

Tampa, FL · On-site

Establish best practices for annotation quality management, training data curation, active learning ... services at scale. * Proficiency in SQL with strong working knowledge of Oracle databases for ...

JPMorgan Chase & Co

Data Scientist Lead

Tampa, FL · On-site

Establish best practices for annotation quality management, training data curation, active learning ... services at scale. * Proficiency in SQL with strong working knowledge of Oracle databases for ...

AIS, Inc.

Data Scientist

Miami, FL · On-site

S., Inc. (AIS) is a national scientific services firm supporting maritime activities requiring ... Support annotation of datasets and development of machine learning models, including training and ...

J.P. Morgan

Data Scientist Lead

Tampa, FL · On-site

Establish best practices for annotation quality management, training data curation, active learning ... services at scale. * Proficiency in SQL with strong working knowledge of Oracle databases for ...

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Data Annotation Services information

What are data annotation services?

Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.

What are the key skills and qualifications needed to thrive in data annotation services?

To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.

What are some common challenges faced when working in data annotation services, and how can I address them?

In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.

What is the difference between Data Annotation Services vs Data Labeling Specialists?

AspectData Annotation ServicesData Labeling Specialists
CredentialsTypically no formal credentials required; focus on trainingOften have training in specific tools or industry standards
Work EnvironmentCollaborative, often remote or in-office teamsSimilar, working in teams or independently on labeling tasks
Industry UsageUsed by AI/ML companies for training datasetsEmployed in similar settings, focusing on labeling data for AI models
Search & Comparison IntentUnderstanding services offered for data preparationLooking for roles or tasks related to data labeling

Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.

What are popular job titles related to Data Annotation Services jobs in Florida?

For Data Annotation Services jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Data Annotation Services jobs in Florida look for?

The top searched job categories for Data Annotation Services jobs in Florida are:

What cities in Florida are hiring for Data Annotation Services jobs?

Cities in Florida with the most Data Annotation Services job openings:

Data Annotation Services jobs near you
Infographic showing various Data Annotation Services job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Data Scientist Lead

JP Morgan Chase

Tampa, FL

Full-time

Medical, Retirement

Posted 22 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 499 frontline employees who took The Breakroom Quiz

72nd of 174 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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