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Artificial Intelligence Data Annotation Jobs in Florida

Alivi

Director of Business Intelligence

Miami, FL · On-site

Continuously improve reporting environments to enhance user experience, adoption, and data accessibility. Advanced Analytics, Artificial Intelligence & Innovation * Guide the development of ...

Akerman

Director of Artificial Intelligence

Miami, FL · On-site

Akerman LLP, an AmLaw 100 firm, is seeking a hands-on Director of Artificial Intelligence to lead ... Build the data and tooling backbone. Develop production-grade pipelines and tools that collect and ...

Akerman

Director of Artificial Intelligence

Orlando, FL · On-site

Akerman LLP, an AmLaw 100 firm, is seeking a hands-on Director of Artificial Intelligence to lead ... Build the data and tooling backbone. Develop production-grade pipelines and tools that collect and ...

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All JobsArtificial Intelligence Data Annotation JobsArtificial Intelligence Data Annotation Jobs in Florida

Artificial Intelligence Data Annotation information

See Florida salary details

$19.5K

$77.7K

$151K

How much do artificial intelligence data annotation jobs pay per year?

As of Aug 10, 2026, the average yearly pay for artificial intelligence data annotation in Florida is $77,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,245.00 and $108,735.00 per year, depending on experience, location, and employer.

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

To thrive as an Artificial Intelligence Data Annotation specialist, you need strong attention to detail, proficiency in data labeling, and a basic understanding of machine learning concepts, often supported by a high school diploma or higher. Familiarity with annotation platforms (such as Labelbox or CVAT), spreadsheet software, and sometimes knowledge of programming basics or data formats (like CSV or JSON) is beneficial. Strong communication skills, consistency, and the ability to work both independently and collaboratively are key soft skills for this role. These competencies ensure high-quality, accurate datasets that are critical for training reliable AI models.

How to become an artificial intelligence data annotation?

To become an AI data annotation specialist, you typically need strong attention to detail, basic computer skills, and familiarity with annotation tools or platforms. Some roles may require a high school diploma or equivalent, and training is often provided on the job. Developing skills in data labeling, understanding of AI concepts, and consistency are key to success in this field.

What does an artificial intelligence data annotation do?

Daily responsibilities for an Artificial Intelligence Data Annotation professional typically include reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them according to project guidelines. You may also participate in quality assurance checks, provide feedback to improve annotation processes, and collaborate with data scientists or project managers to clarify labeling standards. Most annotation work requires maintaining strict attention to detail and meeting production quotas or deadlines. Work is often structured individually but may involve collaboration within a larger team, especially when aligning on new guidelines or best practices. This structured, detail-oriented environment supports the development of high-quality training data for AI systems.

What is an artificial intelligence data annotation?

An Artificial Intelligence Data Annotation job involves labeling, tagging, or categorizing data such as text, images, audio, or video to train machine learning models. Annotators help improve AI accuracy by providing high-quality, structured data that algorithms use to learn patterns. Tasks may include bounding box annotation, sentiment analysis, transcription, or entity recognition, depending on the AI application. This role is essential in industries like autonomous vehicles, healthcare, and natural language processing. Attention to detail and familiarity with annotation tools are key skills for this job.

What are the most commonly searched types of Artificial Intelligence Data Annotation jobs in Florida? The most popular types of Artificial Intelligence Data Annotation jobs in Florida are:
What are popular job titles related to Artificial Intelligence Data Annotation jobs in Florida? For Artificial Intelligence Data Annotation jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Data Annotation jobs in Florida look for? The top searched job categories for Artificial Intelligence Data Annotation jobs in Florida are:
What cities in Florida are hiring for Artificial Intelligence Data Annotation jobs? Cities in Florida with the most Artificial Intelligence Data Annotation job openings:
Artificial Intelligence Data Annotation jobs near you
Infographic showing various Artificial Intelligence Data Annotation job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $77,709 per year, or $37.4 per hour.

Director of Business Intelligence

Alivi

Miami, FL • On-site

Full-time

Posted 27 days ago

Job description

SUMMARY
The Director of Business Intelligence is responsible for defining and executing the organization's enterprise data and analytics strategy to enable data-driven decision-making across all business functions. This leader provides strategic oversight of Business Intelligence, Data Engineering, Data Governance, and Analytics while partnering with executive leadership to transform enterprise data into measurable business value.
DUTIES & RESPONSIBILITIES
Enterprise Data Strategy & Leadership
  • Serve as the enterprise leader for data governance, data quality, data security, and data management best practices.
  • Establish and maintain enterprise data standards, policies, and procedures.
  • Lead a team of BI developers, data engineers, data analysts, and architects.
  • Partner with executive leadership to identify opportunities where analytics can drive operational and financial performance.
  • Develop and manage BI roadmaps, project portfolios, resource planning, and departmental budgets.

Data Warehouse & Data Lake Architecture
  • Develop scalable data platforms capable of integrating structured and unstructured data from internal and external sources.
  • Lead the development of modern ELT/ETL frameworks and data pipelines.
  • Ensure data models support operational reporting, executive dashboards, predictive analytics, and self-service business intelligence.
  • Establish data lineage, metadata management, master data management, and data cataloging standards.
  • Optimize data storage, performance, scalability, and data accessibility across the organization.

Data Engineering & Data Management
  • Direct enterprise-wide data integration initiatives involving financial, operational, clinical, customer, and third-party systems.
  • Ensure the accuracy, completeness, consistency, and reliability of organizational data assets.
  • Implement processes to monitor data quality and proactively resolve data integrity issues.
  • Oversee data migration, transformation, validation, and reconciliation activities.
  • Establish data retention, archival, security, and compliance standards.
  • Evaluate emerging technologies and platforms to improve enterprise data capabilities.

Business Intelligence, Reporting & Self-Service Analytics
  • Lead the design, development, and deployment of executive dashboards, scorecards, and interactive reporting solutions.
  • Establish enterprise KPI frameworks and performance management metrics.
  • Develop self-service analytics capabilities using modern BI tools.
  • Ensure dashboards provide actionable insights and support strategic, tactical, and operational decision-making.
  • Partner with business stakeholders to gather requirements and translate business needs into scalable reporting solutions.
  • Continuously improve reporting environments to enhance user experience, adoption, and data accessibility.

Advanced Analytics, Artificial Intelligence & Innovation
  • Guide the development of predictive, prescriptive, and diagnostic analytics solutions.
  • Lead initiatives focused on trend analysis, forecasting, segmentation, profitability analysis, resource optimization, and operational performance.
  • Provide strategic recommendations based on complex analyses and business intelligence findings.
  • Drive organization-wide adoption of data-driven decision-making practices.
  • Present analytical findings and business recommendations to executive leadership and key stakeholders.

Operational and Financial Analytics
  • Support financial performance initiatives through advanced reporting and analytics.
  • Develop enterprise reporting for revenue, profitability, cost management, utilization, productivity, and operational effectiveness.
  • Monitor key performance indicators and identify opportunities for process improvement.
  • Collaborate with Finance, Operations, Compliance, and Business Development teams to support strategic initiatives.

Stakeholder Management
  • Partner with business leaders to identify analytics opportunities and prioritize BI initiatives.
  • Act as a trusted advisor to executive leadership on data strategy and business intelligence matters.
  • Communicate complex technical concepts and analytical findings to both technical and non-technical audiences.
  • Foster a culture of collaboration, innovation, and continuous improvement across the organization.

REQUIREMENTS & QUALIFICATIONS
Education
  • Bachelor's degree in computer science, Information Systems, Data Analytics, Business Intelligence, Engineering, Mathematics, or related field required.
  • Master's degree preferred.

Experience
  • 8+ years of progressive experience in Business Intelligence, Data Engineering, Data Architecture, Analytics, or related disciplines.
  • 5+ years of leadership experience managing BI, Analytics, or Data Engineering teams.
  • Experience designing and managing enterprise Data Warehouses and Data Lakes.
  • Proven experience leading enterprise-scale data transformation initiatives.
  • Experience supporting executive leadership with strategic reporting and analytics.

Technical Skills
  • Advanced SQL expertise.
  • Data Warehouse Architecture (Kimball, Star Schema, Snowflake Models).
  • Data Lake and Modern Data Platform Architecture.
  • Data Modeling and Database Design.
  • ETL/ELT Development and Data Integration.
  • Microsoft SQL Server, Azure, AWS, Snowflake, Databricks, or equivalent cloud platforms.
  • Data Governance and Master Data Management.
  • Python, R, or other analytics programming languages preferred.
  • Agile project management methodologies.

COMPETENCIES
Strategic Leadership
  • Develop long-term data and analytics strategies aligned with organizational goals.
  • Drives enterprise-wide adoption of data-driven decision-making.

Data Architecture & Management
  • Designs scalable and sustainable data environments.
  • Ensures strong governance, quality, security, and accessibility of data assets.

Business Intelligence
  • Translate complex business requirements into impactful dashboards and reporting solutions.
  • Establish meaningful KPIs and performance monitoring systems.

Analytical Thinking
  • Synthesizes complex data into actionable business insights.
  • Identifies trends, risks, opportunities, and operational improvements.

Project & Program Management
  • Leads large-scale cross-functional initiatives.
  • Effectively manages priorities, resources, timelines, and stakeholder expectations.

Communication & Executive Presence
  • Influences decision-making through data storytelling and strategic recommendations.
  • Effectively communicates with executive leadership, board members, clients, and operational teams.

Innovation & Continuous Improvement
  • Champions emerging technologies and modern analytics practices.
  • Continuously improves data platforms, reporting capabilities, and organizational analytics maturity.

HOW WE BEHAVE: CORE VALUES
  • Collaborative - We are friendly, and always ready to lend a hand; We are humble, and willing to admit mistakes; We trust our team and use respectful conflict to make decisions.
  • Entrepreneurial - We are personally committed, and hunger for Alivi's success; We show passion and do more with what we have; We don't give up and always find ways to get the job done.
  • Dynamic - We gladly welcome change; We are smart, and challenge how things are done. We adapt quickly, and readily embrace new roles, and projects.

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