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Data Analyst Ai Jobs in Indiana (NOW HIRING)

PinnaclePartners

Jr Data Analyst

Indianapolis, IN

$40K - $45K/yr

Jr. Data Analyst Location: Onsite - Indianapolis, IN Pay: Up to $45K Direct Hire Pinnacle Partners ... or AI assistants like Claude Maintain strict confidentiality when handling sensitive customer ...

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Data Analyst Ai information

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.

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 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.

What does a data analyst do in AI?

A data analyst in AI collects, cleans, and analyzes large datasets to identify patterns and insights that improve machine learning models and AI systems. They often use tools like Python, R, or SQL and work closely with data scientists to support model development and validation.

Do data analysts work with AI?

Data analysts often work with AI by analyzing data used to train machine learning models, developing insights, and creating reports that support AI projects. They may also use tools like Python, R, or SQL to process large datasets and collaborate with data scientists and AI engineers. Understanding AI concepts can enhance their ability to interpret and leverage AI-driven insights.
What are the most commonly searched types of Data Analyst Ai jobs in Indiana? The most popular types of Data Analyst Ai jobs in Indiana are:
What are popular job titles related to Data Analyst Ai jobs in Indiana? For Data Analyst Ai jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Analyst Ai jobs in Indiana look for? The top searched job categories for Data Analyst Ai jobs in Indiana are:
What cities in Indiana are hiring for Data Analyst Ai jobs? Cities in Indiana with the most Data Analyst Ai job openings:
Data Analyst Ai jobs near you
Infographic showing various Data Analyst Ai job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

IT Analyst, AI Engineer

Patrick Industries

Elkhart, IN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

Patrick Industries rating

6.3

Company rating: 6.3 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

487th of 537 rated manufacturers

Job description

Patrick Industries, a publicly traded company headquartered in Elkhart, Indiana, invites you to join a team of dedicated Team Members who are passionate about delivering high-quality products and exceptional customer service. As a leading solutions provider serving a diverse range of markets across the United States, our commitment to innovation, quality, and sustainability has positioned us as a high growth, diversified and empowered Team of more than 10,000! Your adventure awaits!

The IT Analyst, AI Engineer is responsible for designing, building, testing, deploying, and supporting AI-enabled applications, integrations, and agentic solutions across Patrick Industries. As a hands-on engineering role within the Agile AI Factory, this position develops production-ready AI capabilities that automate business processes, enhance decision-making, and integrate AI technologies with enterprise systems. The AI Engineer partners closely with product managers, platform engineers, data engineers, and business stakeholders to deliver scalable, secure, and reliable AI solutions that support enterprise objectives.

Responsibilities & Duties:

AI Solution Development

  • Design, develop, test, and deploy AI-enabled applications, agents, and automation solutions
  • Build production-ready software components that support enterprise AI initiatives
  • Implement AI workflows, agent orchestration, prompt engineering, and retrieval-augmented generation capabilities
  • Translate business and technical requirements into scalable software solutions
  • Develop reusable components and integration patterns that accelerate future AI delivery
  • Create and maintain technical documentation for solutions, integrations, and development standards

Application & Systems Integration

  • Build integrations between AI platforms and enterprise systems, including ERP, business applications, and operational technologies
  • Develop APIs, services, and integration layers that enable secure and reliable information exchange
  • Support connectivity between AI solutions, data platforms, and business applications
  • Troubleshoot integration issues impacting delivery, performance, and production stability
  • Ensure integrations align with enterprise architecture and security standards
  • Collaborate with business and technical teams to support end-to-end solution delivery

Data Engineering & AI Enablement

  • Develop data pipelines and supporting infrastructure required for AI applications and workflows
  • Partner with Data Engineering teams to ensure data quality, availability, and readiness
  • Support ingestion, transformation, and preparation of data for AI and analytics use cases
  • Design solutions that optimize data accuracy, performance, and scalability
  • Assist with implementation of enterprise AI and data platform standards
  • Support AI model utilization through reliable data architecture and engineering practices

Solution Quality, Testing & Monitoring

  • Develop and maintain test cases, evaluation criteria, and regression testing processes for AI solutions
  • Validate AI outputs and ensure solution quality meets business and technical requirements
  • Implement monitoring and observability standards for AI applications, workflows, and integrations
  • Monitor latency, performance, reliability, and output quality in production environments
  • Support issue resolution, defect remediation, and ongoing production support activities
  • Continuously improve solution stability and operational performance

DevOps & Agile Delivery

  • Apply DevOps best practices including CI/CD, source control, automated testing, and release management
  • Participate in sprint planning, backlog refinement, stand-ups, reviews, and retrospectives
  • Collaborate with cross-functional delivery teams to execute prioritized work
  • Provide effort estimates, status updates, and risk identification for assigned initiatives
  • Support deployment planning, release execution, and production readiness activities
  • Follow enterprise governance, security, and responsible AI standards throughout development

Engineering Design & Technical Contribution

  • Contribute to solution architecture discussions and engineering design decisions within assigned projects
  • Identify and communicate technical trade-offs related to cost, scalability, performance, reliability, and maintainability
  • Evaluate technical feasibility and support development of implementation approaches
  • Escalate architectural concerns and solution risks when appropriate
  • Recommend improvements to development standards, tools, and engineering practices
  • Stay current on emerging AI technologies, frameworks, and software engineering techniques

AI Initiative Execution

  • Deliver technology solutions that support enterprise AI priorities and business transformation efforts
  • Contribute to automation, intelligent workflow, analytics, and AI-enabled business initiatives
  • Support development of capabilities across operations, supply chain, manufacturing, finance, and corporate functions
  • Assist with measurement and monitoring of solution adoption and business impact
  • Collaborate with Product Managers and business stakeholders to ensure delivered solutions achieve intended outcomes

Qualifications and Skills:

  • Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or related field; equivalent experience may be considered
  • 2+ years of software engineering, data engineering, AI engineering, or related experience
  • Experience designing, building, testing, and supporting software applications and integrations
  • Experience with AI, machine learning, generative AI, agent-based systems, or intelligent automation solutions
  • Proficiency with Python, SQL, and JavaScript/TypeScript or similar development languages
  • Knowledge of prompt engineering, AI orchestration frameworks, and retrieval-augmented generation concepts
  • Experience with APIs, system integrations, and enterprise application connectivity
  • Experience with version control systems, automated testing, and CI/CD practices
  • Familiarity with Agile development methodologies including Scrum and Kanban
  • Understanding of software architecture, system design, and engineering best practices
  • Experience with Microsoft Azure, Microsoft Fabric, Microsoft Foundry, Azure DevOps, and Dynamics 365 environments preferred
  • Familiarity with monitoring, observability, and application performance management concepts
  • Experience integrating AI solutions with enterprise systems and business processes preferred
  • Exposure to manufacturing, operations, supply chain, or industrial environments preferred
  • Experience in decentralized, multi-site, or acquisition-driven organizations preferred
  • Familiarity with MLOps, model deployment, monitoring, and lifecycle management is a plus
  • Exposure to C#, Rust, or KQL is a plus
  • Strong analytical, problem-solving, communication, and collaboration skills

 

Benefits Include:

Health, Dental, Vision, Life, Insurances, Paid Vacation, 401K Match, Holidays, Health Club and Tuition Reimbursement

At Patrick Industries, BETTER Together is our commitment to being our best while striving to bring out the best in one another as we join forces Individually, as Teams, with our Business Units, with our Customers, our Communities and within our entire Patrick family.

Patrick is an Equal Opportunity Employer.

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