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Generative Ai Analyst information

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$46.6K

$84.3K

$117.5K

How much do generative ai analyst jobs pay per year?

As of Sep 8, 2026, the average yearly pay for generative ai analyst in Indiana is $84,279.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,900.00 and $94,700.00 per year, depending on experience, location, and employer.

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.

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.

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.

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. Senior roles or those with specialized skills in machine learning and deep learning can command higher salaries, often exceeding $150,000.

Is Generative AI a promising career?

Generative AI is a rapidly growing field with increasing demand for specialists such as Generative AI Analysts, who develop and refine AI models like GPT and DALL·E. Careers in this area often require skills in machine learning, programming, and data analysis, and offer opportunities across technology, healthcare, entertainment, and other industries. The field is expected to continue expanding as AI applications become more integrated into various sectors.

What are popular job titles related to Generative Ai Analyst jobs in Indiana?

For Generative Ai Analyst jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Generative Ai Analyst jobs in Indiana look for?

The top searched job categories for Generative Ai Analyst jobs in Indiana are:

Generative Ai Analyst jobs near you
Infographic showing various Generative Ai Analyst job openings in Indiana as of August 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 63% Physical, 5% Hybrid, and 32% Remote job distribution, with an average salary of $84,279 per year, or $40.5 per hour.

Generative AI Engineer

Prophecy Technologies

Indianapolis, IN • On-site

Full-time

Posted 7 days ago

Job description

Role Overview:
Design, engineer, and implement enterprise-scale AI/ML and generative AI solutions for clinical data workflows. This role requires delivering secure, scalable architectures independently while maintaining accountability for project delivery and technical excellence.
Key Responsibilities:
  • Conceive, design, and implement AI solutions; analyze workflows and devise innovative technical approaches.
  • Design secure, scalable architectures for AI/ML, generative AI, and agentic solutions.
  • Design and implement emerging AI technologies such as RAG, agentic workflows, and agent-to-agent communication.
  • Build and deploy predictive analytics and generative AI solutions to production environments.
  • Develop robust data/model pipelines, APIs, and integration layers; establish AI/MLOps best practices.
  • Implement CI/CD, monitoring, and observability for AI/ML systems.
  • Own project scope and delivery accountability.

Required Skills:
  • Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda, RDS, Glue, Athena, DynamoDB, Postgres), Databricks (Platform, Delta Lake, Spark, MLflow, SQL).
  • Programming Languages & ML: Python, PySpark, SQL.
  • DevOps & Infrastructure: Git, CI/CD, Docker, Kubernetes, IaC (Terraform/CloudFormation).
  • AI/Data Technologies: Generative AI frameworks, Large Language Models (LLMs), vector databases, Apache Spark.

Qualifications:
  • Bachelor's degree (BS) in Computer Science, Engineering, Mathematics, Statistics or equivalent professional experience.
  • 5+ years of experience in software, data, or ML engineering.
  • 3+ years of experience deploying ML solutions in production environments.

Preferred Skills:
  • Digital Artificial Intelligence (AI) expertise.

Apply