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Data Analyst Ai Jobs in Boca Raton, FL (NOW HIRING)

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$32.3K

$78.4K

$129.1K

How much do data analyst ai jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data analyst ai in Boca Raton, FL is $78,423.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,300.00 and $92,000.00 per year, depending on experience, location, and employer.

What is a data analyst AI?

A Data Analyst AI is a professional who uses artificial intelligence tools and techniques to analyze and interpret complex data sets. They leverage machine learning algorithms, statistical models, and data visualization tools to uncover trends, patterns, and insights that help organizations make data-driven decisions. In addition to traditional data analysis skills, Data Analyst AI professionals are proficient in programming languages like Python or R and are familiar with AI frameworks. Their work often involves cleaning and preparing data, building predictive models, and communicating findings to stakeholders. This role bridges the gap between data analysis and AI-driven solutions.

What are the key skills and qualifications needed to thrive as a data analyst AI, and why are they important?

To thrive as a Data Analyst AI, you need strong analytical skills, proficiency in statistics, data visualization, and a solid understanding of machine learning principles, often supported by a degree in a quantitative field. Familiarity with tools such as Python, SQL, R, and AI platforms like TensorFlow or PyTorch, as well as certifications in data analytics or AI, is highly beneficial. Critical thinking, attention to detail, and effective communication help you interpret data insights and present findings to stakeholders. These skills are crucial for extracting meaningful patterns from complex datasets and enabling data-driven decision-making in AI-driven environments.

How does a data analyst AI typically collaborate with data scientists and engineering teams?

Data Analysts focusing on AI often work closely with data scientists to prepare, clean, and analyze large datasets that feed into machine learning models. They also collaborate with engineering teams to ensure data pipelines are robust and scalable, supporting both ongoing analysis and model deployment. Regular communication and documentation are essential, as insights and findings from the analyst's work often inform model improvements and business decisions. This cross-functional teamwork helps bridge the gap between raw data and actionable AI solutions.

What is the difference between Data Analyst Ai vs Data Scientist?

AspectData Analyst AiData Scientist
Required CredentialsBachelor's in Data Science, Analytics, or related field; certifications like Microsoft Certified Data AnalystBachelor's or Master's in Data Science, Statistics, or related; advanced certifications often preferred
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development, modeling, and complex data analysis
Employer & Industry UsageCorporate, finance, marketing, healthcareTech companies, research institutions, finance, healthcare
Common Search & ComparisonOften compared for entry to mid-level roles in data analysisMore advanced, requiring deeper statistical and machine learning skills

Data Analyst Ai and Data Scientist roles share overlapping skills but differ mainly in complexity and scope. Data Analysts Ai focus on interpreting data and creating reports, while Data Scientists develop models and algorithms for predictive analytics. Understanding these differences helps in career planning and job targeting.

What does a data analyst do in AI?

A data analyst in AI collects, cleans, and analyzes large datasets to identify patterns and insights that improve machine learning models and AI systems. They often use tools like Python, R, or SQL and work closely with data scientists to support model development and validation.

Do data analysts work with AI?

Data analysts often work with AI by analyzing data used to train machine learning models, developing insights, and creating reports that support AI projects. They may also use tools like Python, R, or SQL to process large datasets and collaborate with data scientists and AI engineers. Understanding AI concepts can enhance their ability to interpret and leverage AI-driven insights.
What are the most commonly searched types of Data Analyst Ai jobs in Boca Raton, FL? The most popular types of Data Analyst Ai jobs in Boca Raton, FL are:
What are popular job titles related to Data Analyst Ai jobs in Boca Raton, FL? For Data Analyst Ai jobs in Boca Raton, FL, the most frequently searched job titles are:
What job categories do people searching Data Analyst Ai jobs in Boca Raton, FL look for? The top searched job categories for Data Analyst Ai jobs in Boca Raton, FL are:
What cities near Boca Raton, FL are hiring for Data Analyst Ai jobs? Cities near Boca Raton, FL with the most Data Analyst Ai job openings:
Data Analyst Ai jobs near you
Infographic showing various Data Analyst Ai job openings in Boca Raton, FL as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $78,423 per year, or $37.7 per hour.

Technical Architect - Data, Analytics & AI

Munich Re

Fort Lauderdale, FL • Hybrid

$61 - $78.50/hr

Full-time

Medical, Life, Retirement, PTO

Re-posted 4 days ago

Job description

Location: Princeton, New Jersey Hybrid 40-50% onsite 

Role Overview

We are seeking a Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Technical Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Technical Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
  • Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWS  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position is $141,800 - $207,900 plus opportunity for company bonus based upon a percentage of eligible pay.  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO). 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range. 

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