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Ai Risk Analyst Jobs in Georgia (NOW HIRING)

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business ... The AI Data Analyst partners with data engineering, AI, and governance teams to assess data ...

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business ... The AI Data Analyst partners with data engineering, AI, and governance teams to assess data ...

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business ... The AI Data Analyst partners with data engineering, AI, and governance teams to assess data ...

Design and enhance risk assessment methodologies utilizing AI, machine learning, predictive analytics, and scenario modeling techniques. * Develop automated workflows, dashboards, and reporting ...

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Ai Risk Analyst information

See Georgia salary details

$12

$34

$55

How much do ai risk analyst jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for ai risk analyst in Georgia is $34.19, according to ZipRecruiter salary data. Most workers in this role earn between $25.19 and $41.59 per hour, depending on experience, location, and employer.

How does an AI Risk Analyst typically collaborate with cross-functional teams to assess and mitigate risks?

AI Risk Analysts work closely with data scientists, engineers, compliance officers, and business leaders to identify, evaluate, and mitigate risks associated with AI systems. They facilitate risk assessment workshops, gather input from technical and non-technical stakeholders, and ensure that risk controls are integrated into AI development processes. Effective communication and documentation are crucial, as analysts must translate complex technical risks into actionable recommendations for diverse teams. This collaborative approach helps ensure that AI solutions are both innovative and aligned with regulatory and ethical standards.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as AI research directors, chief AI officers, or senior data scientists working in organizations with significant AI investments. These positions often require advanced skills in machine learning, deep learning, and data analysis, along with extensive experience and leadership responsibilities. Compensation at this level reflects the strategic importance and complexity of AI initiatives within the company.

What careers are at risk with AI?

AI poses a risk to jobs involving repetitive tasks and routine processes, such as data entry, basic customer service, and certain manufacturing roles. Roles that rely heavily on manual or predictable tasks are more susceptible to automation, while jobs requiring complex decision-making, creativity, and emotional intelligence are less vulnerable.

How to become an AI risk analyst?

To become an AI risk analyst, candidates typically need a strong background in computer science, data analysis, or related fields, along with knowledge of AI systems and risk management principles. Relevant skills include programming, statistical analysis, and familiarity with AI safety tools, often supported by certifications or advanced degrees. Gaining experience through internships or projects focused on AI ethics and safety is also beneficial.

What does an AI risk analyst do?

An AI risk analyst evaluates potential risks associated with artificial intelligence systems, including ethical, safety, and security concerns. They analyze data, develop risk mitigation strategies, and often use tools like risk assessment frameworks and programming skills to ensure AI deployments are safe and compliant with regulations.

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

AspectAi Risk AnalystData Scientist
Required CredentialsBachelor's in Risk Management, Data Science, or related fields; certifications in AI or risk analysisBachelor's or Master's in Data Science, Statistics, or Computer Science; certifications in data analysis or machine learning
Work EnvironmentFinancial institutions, insurance companies, or tech firms focusing on risk assessmentTech companies, research labs, or any industry leveraging data for insights
Employer & Industry UsagePrimarily in finance, insurance, and risk-focused sectorsAcross various industries including tech, healthcare, finance, and marketing

The main difference is that an Ai Risk Analyst specializes in assessing and managing risks related to AI systems, often within financial or risk-focused industries. In contrast, a Data Scientist analyzes large datasets to extract insights across diverse sectors. While both roles require strong analytical skills and knowledge of AI and data tools, the Ai Risk Analyst focuses more on risk mitigation specific to AI applications.

What are the key skills and qualifications needed to thrive as an AI Risk Analyst, and why are they important?

To thrive as an AI Risk Analyst, you need a strong foundation in data analysis, risk assessment, and an understanding of AI/ML technologies, typically supported by a degree in computer science, statistics, or a related field. Familiarity with risk management frameworks, AI auditing tools, and certifications such as CRISC or AI ethics credentials is often required. Excellent problem-solving, critical thinking, and communication skills help in identifying risks and conveying complex findings to stakeholders. These skills are crucial to ensure responsible AI deployment, mitigate potential risks, and maintain regulatory compliance.

What are AI Risk Analysts?

AI Risk Analysts are professionals who assess, monitor, and manage the risks associated with the development and deployment of artificial intelligence systems. Their work involves identifying potential threats such as bias, security vulnerabilities, ethical concerns, and compliance issues that could arise from using AI technologies. They collaborate with data scientists, engineers, and compliance teams to develop risk mitigation strategies and ensure that AI systems operate safely, ethically, and in accordance with relevant regulations.
What cities in Georgia are hiring for Ai Risk Analyst jobs? Cities in Georgia with the most Ai Risk Analyst job openings:
Infographic showing various Ai Risk Analyst job openings in Georgia as of July 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $71,105 per year, or $34.2 per hour.
AI Data Analyst

AI Data Analyst

LexisNexis

Alpharetta, GA • On-site

Full-time

Medical, Life

Posted 29 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

162nd of 451 rated business services


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 AI-ready 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 end-to-end data pipelines and is not expected to be a deep technical expert in RAG or embeddings, but should have a solid working understanding of AI-driven 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 AI-consumed 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, well-scoped 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 AI-consumed data with enterprise governance requirements, including classification, access controls, and retention.
  • Support basic data lineage and ownership documentation for AI-relevant 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 end-to-end 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 non-technical stakeholders.

Preferred Qualifications
  • Exposure to AI-enabled products, copilots, or search-based 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, up-to-date, 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 Form or please contact 1-855-833-5120.
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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.
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