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Data Analyst Ai Jobs (NOW HIRING)

RELX

AI Data Analyst

Boca Raton, FL

We are seeking an AI Data Analyst to support teams in preparing and maintaining AIready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality ...

Hayden AI

Data Analyst

San Francisco, CA · On-site

$123K - $160K/yr

Hayden AI seeks a Data Analyst to support a diverse set of stakeholders with Data and Analytics ... needs. This is a great opportunity for someone who wants to deliver a big impact: you'll be ...

LP Analyst

Data Analyst - Data Operations

Dallas, TX · On-site

Job Summary : LP Analyst is a leading independent private asset cloud-based analytics and ... Leverage AI-based tools for automated data extraction and validation, helping to assess output ...

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How much do data analyst ai jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data analyst ai in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 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.

Can AI do the job of a data analyst?

AI can automate many tasks performed by data analysts, such as data cleaning, basic analysis, and reporting, using tools like machine learning algorithms and data visualization software. However, human skills in interpreting complex data, making strategic decisions, and understanding business context remain essential for comprehensive analysis. Data analysts often use AI as a tool to enhance productivity but still require critical thinking and domain expertise.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior data scientist or AI research director, often requiring advanced skills in machine learning, deep learning, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms with competitive compensation packages.

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 specializing in 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.

Which 3 jobs will survive AI?

Data Analysts with expertise in AI and machine learning are likely to continue thriving as organizations rely on data-driven decision-making. Roles such as healthcare professionals and skilled tradespeople are also expected to remain in demand due to the need for human judgment and physical skills that AI cannot replicate. These jobs typically require specialized knowledge, critical thinking, and adaptability to technological changes.

What do AI data analysts do?

AI data analysts collect, process, and analyze large datasets to extract insights that inform AI models and business decisions. They use tools like SQL, Python, and machine learning frameworks to clean data, develop algorithms, and evaluate model performance, often working closely with data scientists and engineers.
More about Data Analyst Ai jobs
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Data Analyst Ai jobs near you
Infographic showing various Data Analyst Ai job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
AI Data Analyst

AI Data Analyst

RELX

Boca Raton, FL

Full-time

Medical, Life

Posted 20 days ago

Job description

Are you passionate about improving data quality and readiness to unlock the full potential of AI solutions?

Do you enjoy collaborating across teams to ensure data is structured, governed, and usable for intelligent systems?

About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,

https://risk.lexisnexis.com

About the Team:

We are a newly formed Enterprise AI team focused on enabling agent-based solutions across the organization. We build and manage the environments, platforms, and guardrails that allow teams to create, test, and scale AI agents safely and efficiently turning experimentation into real business impact.

We're a team of curious builders and operators who are constantly exploring, learning, and applying new AI tools and approaches to solve real-world problems and improve how work gets done.

About the Role:

We are seeking an AI Data Analyst to support teams in preparing and maintaining AIready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality, metadata, and governance, helping teams understand how to structure, document, and manage their data so it can be safely and effectively used by AI systems.

The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own endtoend data pipelines and is not expected to be a deep technical expert in RAG or embeddings, but should have a solid working understanding of AIdriven data needs.

Responsibilities:

AI Data Readiness Support

  • Work with product and delivery teams to assess whether datasets and content are fit for AI use cases.
  • Help teams understand and apply AI data readiness standards, including quality, freshness, metadata, and access expectations.
  • Identify common data issues that impact AI outcomes (e.g., stale data, unclear ownership, missing metadata) and recommend remediation steps.
  • Contribute to repeatable checklists, guidance, or documentation that help teams prepare data for AI.

Data Quality & Relevance

  • Support data quality checks focused on accuracy, completeness, consistency, and timeliness for AIconsumed data.
  • Assist in monitoring and validating data freshness and relevance, escalating issues to engineering or data owners as needed.
  • Help teams improve data clarity and usability to reduce ambiguity in AI outputs.

Metadata & Semantic Enablement

  • Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content.
  • Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning (in coordination with engineering teams).
  • Promote good content hygiene practices (clear structure, consistent naming, wellscoped documents).

AI Data Sources & Retrieval (Support Role)

  • Support the upkeep and documentation of approved data sources used by AI solutions.
  • Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.
  • Collaborate with AI and platform teams on data inclusion/exclusion decisions without owning technical implementation.

Governance, Lineage & Compliance Awareness

  • Help teams align AIconsumed data with enterprise governance requirements, including classification, access controls, and retention.
  • Support basic data lineage and ownership documentation for AIrelevant datasets.
  • Partner with governance and security teams by surfacing risks or gaps; does not act as final approval authority.

What This Role Does Not Own

  • Does not design or own endtoend production data pipelines.
  • Does not act as the primary technical owner for RAG frameworks, vector databases, or embedding strategies.
  • Does not make final governance or compliance decisions independently.

Requirements:

  • Proven experience in data analysis, analytics engineering, data operations, or data quality roles.
  • Good understanding of data quality principles and how poor data impacts downstream systems.
  • Experience working with structured and unstructured data (tables, files, documents, knowledge assets).
  • Proficiency in SQL and comfort investigating data issues.
  • Familiarity with data governance fundamentals (classification, access controls, ownership, retention).
  • Strong communication skills and ability to explain data concepts to nontechnical stakeholders.

Preferred Qualifications

  • Exposure to AIenabled products, copilots, or searchbased solutions.
  • Basic familiarity with AI data concepts such as semantic search, embeddings, or retrieval patterns.
  • Experience working in enterprise or regulated environments.
  • Experience contributing to standards, playbooks, or shared data practices.

What Success Looks Like

  • Teams can reliably prepare datasets that meet AI readiness expectations with less rework.
  • AI solutions benefit from more relevant, uptodate, and understandable data.
  • Clear ownership and documentation exist for data used by AI systems.
  • Strong collaboration between delivery teams, data engineering, and governance.

Working for You:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

  • Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
  • Life Assurance Policies: Providing financial security for your loved ones.
  • Modern Family Benefits: Support for maternity, paternity, and adoption needs.
  • Long Service Award: Recognition for your dedication and loyalty.
  • Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
  • Flexible Benefits Plan : Offering you wider choice of services and products
  • Employee Assistance Program : Access support for personal and work-related challenges.
  • Flexible Working Arrangements: Balance work and personal life effectively.
  • Access to Learning and Development Resources: Empowering your professional growth.

Risk benefit statement
Learn more about the LexisNexis Risk team and how we work: https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000

U.S. National Base Pay Range: $78,800 - $131,300. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Ohio, the base pay range is $74,900 - $124,700. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Formor please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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