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Generative Ai Analyst Jobs (NOW HIRING)

TekCommands Inc

AWS + Generative AI Engineer

Chicago, IL · On-site

$66.75 - $87.50/hr

Develop scalable data pipelines for analytics and AI workloads. * Configure and manage AWS Config ... Mentor engineering teams on AWS and Generative AI technologies. Required Skills * 12-16 years of ...

United Airlines

AWS Generative AI Engineer

Columbia, SC · Hybrid

$60 - $78.75/hr

Problem Solving Analytical Thinking * Stakeholder Management * Innovation Mindset * Agile Delivery * Communication and Collaboration Skills Preferred Qualifications * Bachelors or Masters degree in ...

eTeam

AI/ML Engineer - Generative AI

Manhattan, NY · On-site

... analysis, and problem-solving, along with effective cross-functional communication skills ... generative AI models, agent frameworks, custom orchestrators, enterprise systems, APIs, and third ...

Uncountable

Platform Engineer - Generative AI

New York, NY · On-site

$120K - $160K/yr

... and analyze experimental data. Uncountable's users are solving critical problems in materials ... Strong interest in Generative AI * Solid computer science and software engineering fundamentals ...

SS&C Technologies

Key Responsibilities Generative AI & Prompt Engineering * Design, develop, and optimize ... Analyze structured and unstructured data for GenAI use cases * Translate business requirements into ...

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Showing results 21-40

All JobsGenerative Ai Analyst Jobs

Generative Ai Analyst information

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$49K

$88.6K

$123.5K

How much do generative ai analyst jobs pay per year?

As of Aug 5, 2026, the average yearly pay for generative ai analyst in the United States is $88,569.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $99,500.00 per year, depending on experience, location, and employer.

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

AspectGenerative Ai AnalystData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; certifications in AI/MLBachelor's/Master's in CS, Statistics, or related fields; advanced certifications
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Employer & Industry UsageFocus on developing and refining generative AI modelsAnalyze data, build predictive models, derive insights
Common Search & Comparison IntentUnderstanding roles in AI developmentData analysis and modeling skills

While both roles require strong technical skills and knowledge of AI and data analysis, a Generative Ai Analyst specializes in creating and optimizing generative AI models, whereas a Data Scientist focuses on analyzing data to inform business decisions. The roles often overlap but differ in their primary focus and application within organizations.

What are the key skills and qualifications needed to thrive as a generative AI analyst?

To thrive as a Generative AI Analyst, you need a solid background in data science, machine learning, and statistics, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and experience with large language models or generative adversarial networks (GANs) is typically required. Strong analytical thinking, creativity, and effective communication skills help you interpret complex data and present insights to stakeholders. These skills and qualities are crucial for developing innovative AI solutions, solving business challenges, and driving impactful results.

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

A Generative AI Analyst frequently works alongside data scientists and engineering teams to interpret model outputs, assess data quality, and help translate business objectives into technical requirements. Collaboration usually involves regular meetings to review model performance, troubleshoot issues, and refine algorithms based on real-world feedback. Effective communication and a shared understanding of both AI concepts and business goals are essential, as the analyst often serves as a bridge between technical teams and stakeholders. This collaborative environment fosters continuous learning and innovation, making teamwork a core aspect of the role.

How much do generative AI analysts make?

Generative AI analysts typically earn between $70,000 and $130,000 annually, depending on experience, location, and industry. Entry-level roles may start lower, while experienced professionals with specialized skills in machine learning and natural language processing can earn higher salaries.

What is a generative AI analyst?

A Generative AI Analyst is a professional who specializes in analyzing, designing, and optimizing systems that use generative artificial intelligence models, such as large language models or image generators. Their work involves understanding how these AI models are developed, deployed, and utilized across various applications. They assess data quality, monitor model outputs, evaluate performance, and help improve the effectiveness and ethical use of generative AI technologies. Generative AI Analysts may also provide insights to organizations on best practices, risk management, and innovation opportunities related to AI. Their expertise bridges the gap between data science, AI development, and business strategy.
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Generative Ai Analyst jobs near you
Infographic showing various Generative Ai Analyst job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $88,569 per year, or $42.6 per hour.

AI Analyst with Healthcare Background (Los Angeles, CA W2 10+ yrs)

BridgeNexus Technologies Inc

Los Angeles, CA • On-site

Other

Posted yesterday

New

Job description

Role: AI Analyst with Healthcare Background

Location: Los Angeles, CA

Note: W2

seeking an experienced Artificial Intelligence & Machine Learning (AI/ML) Systems Analyst to bridge the gap between business stakeholders, data scientists, AI/ML engineers, and technology teams. This role will be responsible for analyzing business problems, defining AI/ML solution requirements, evaluating data readiness, supporting model implementation, and ensuring AI solutions align with business objectives, regulatory requirements, and enterprise governance standards. The ideal candidate will possess strong analytical skills, healthcare domain knowledge, and experience working with AI, machine learning, and Generative AI technologies.

Key Responsibilities

Business & Systems Analysis

  • Collaborate with business stakeholders to identify opportunities for AI/ML-driven process improvements and automation.
  • Elicit, analyze, and document business, functional, and non-functional requirements.
  • Create user stories, process flows, use cases, data mappings, and acceptance criteria.
  • Translate business requirements into AI/ML solution specifications.
  • Support backlog grooming, sprint planning, and Agile delivery processes.

AI/ML Solution Analysis

  • Partner with AI/ML engineers and data scientists to define model objectives and success metrics.
  • Analyze data sources and determine data quality, completeness, and readiness for AI initiatives.
  • Support predictive analytics, recommendation systems, NLP, GenAI, and intelligent automation initiatives.
  • Evaluate AI model outputs and assist with validation, testing, explainability, and business adoption.

Data & Analytics

  • Perform data analysis using SQL, Python, Power BI, and reporting tools.
  • Develop dashboards and reporting mechanisms to monitor AI model performance and business outcomes.
  • Support data governance, lineage, quality, and compliance activities.
  • Assist in feature identification and business rule definition for ML models.

AI Governance & Compliance

  • Ensure AI solutions comply with enterprise AI policies, security standards, and regulatory requirements.
  • Support documentation of model governance, auditability, explainability, and risk assessments.
  • Participate in AI solution reviews, testing, and deployment readiness activities.

Stakeholder Engagement

  • Act as a liaison between business teams, product owners, architects, data engineers, and AI/ML engineers.
  • Communicate findings, recommendations, and project status to leadership and project stakeholders.
  • Facilitate workshops, requirement sessions, and solution reviews.

Required Qualifications

Education

  • Bachelor''s degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Engineering, Mathematics, or a related field.
  • Master''s degree preferred.

Experience

  • 5+ years of Systems Analysis, Business Analysis, Product Analysis, or related experience.
  • 2+ years supporting AI/ML, Advanced Analytics, Data Science, or Generative AI initiatives.
  • Experience working within Agile/Scrum delivery environments.
  • Healthcare, insurance, or regulated industry experience preferred.

Technical Skills

  • SQL and relational databases
  • Python or R for analytics
  • Power BI, Tableau, or equivalent reporting tools
  • Machine Learning concepts and model lifecycle understanding
  • Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and prompt engineering concepts
  • Cloud platforms such as Azure, AWS, or Google Cloud Platform
  • Azure AI Services, Azure Machine Learning, or equivalent AI platforms preferred 

Preferred Skills

  • Healthcare benefits, claims, member, provider, or utilization management domain knowledge.
  • Experience with AI governance frameworks and responsible AI practices.
  • Understanding of MLOps concepts, model monitoring, and deployment processes.
  • Knowledge of NLP, Computer Vision, Predictive Analytics, and Agentic AI architectures.
  • Familiarity with Jira, Azure DevOps, Confluence, and Git-based development workflows.

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