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... analytics engineering, data operations, or data quality roles. * Good understanding of data quality ... AI solutions benefit from more relevant, uptodate, and understandable data . * Clear ownership and ...
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... analytics engineering, data operations, or data quality roles. * Good understanding of data quality ... AI solutions benefit from more relevant, uptodate, and understandable data . * Clear ownership and ...
... analytics engineering, data operations, or data quality roles. * Good understanding of data quality ... AI solutions benefit from more relevant, uptodate, and understandable data . * Clear ownership and ...
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Manager, Marketing Technology (AI Data & Analytics)
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Manager, Marketing Technology (AI Data & Analytics)
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Manager, Marketing Technology (AI Data & Analytics)
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Manager, Marketing Technology (AI Data & Analytics)
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Ai Data Analytics information
See salary details
$24.52 - $30.88
10% of jobs
$30.88 - $37.24
6% of jobs
$37.24 - $43.60
7% of jobs
$44.33 is the 25th percentile. Wages below this are outliers.
$43.60 - $49.96
14% of jobs
The median wage is $53.27 / hr.
$49.96 - $56.32
24% of jobs
$60.73 is the 75th percentile. Wages above this are outliers.
$56.32 - $62.67
19% of jobs
$62.67 - $69.03
11% of jobs
$69.03 - $75.39
3% of jobs
$75.39 - $81.75
2% of jobs
$81.75 - $88.11
2% of jobs
$88.11 - $94.47
1% of jobs
$24
$54
$94
How much do ai data analytics jobs pay per hour?
What is a $900000 AI job?
Which 3 jobs will survive AI?
What is the difference between Ai Data Analytics vs Data Scientist?
| Aspect | Ai Data Analytics | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analytics | Bachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred |
| Work Environment | Tech companies, finance, healthcare; focus on AI-driven data analysis | Research labs, tech firms, finance; focus on data modeling and insights |
| Employer & Industry Usage | Used in industries leveraging AI for predictive analytics and automation | Used across industries for data modeling, predictive analytics, and research |
Ai Data Analytics professionals focus on applying AI techniques to analyze data and develop automated solutions, while Data Scientists build models and interpret data to generate insights. Both roles require strong analytical skills and familiarity with data tools, but Ai Data Analytics emphasizes AI implementation, whereas Data Scientists focus on statistical modeling and research.
How does an AI Data Analytics professional typically collaborate with cross-functional teams within an organization?
What is the salary of an AI data analyst?
What are the key skills and qualifications needed to thrive as an AI Data Analyst, and why are they important?
What is AI Data Analytics?
What does an AI data analyst do?

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
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.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.
Please read our Candidate Privacy Policy.
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.
USA Job Seekers:
EEO Know Your Rights.
About LexisNexis Risk Solutions
Sourced by ZipRecruiter
Industry
It services
Company size
1,001 - 5,000 Employees
Headquarters location
Alpharetta, GA, US
Year founded
2000