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Ai Data Analytics Jobs in Michigan (NOW HIRING)

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics. * Optimize cloud infrastructure: Utilize AWS cloud computing platforms to ...

Venteon is currently seeking a Senior Director of Data Analytics & AI to lead enterprise data strategy for a global manufacturing organization. This executive-level position will drive the ...

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

... Data, or Analytics leadership roles * Proven experience building and scaling technical teams or practices * Experience in: * Generative AI technologies (LLMs, RAG pipelines, prompt engineering, API ...

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

... Data, or Analytics leadership roles * Proven experience building and scaling technical teams or practices * Experience in: * Generative AI technologies (LLMs, RAG pipelines, prompt engineering, API ...

Senior Data and AI Specialist

Detroit, MI · On-site

$117K - $150K/yr

Data Science Engineering & Analytics Delivery * Build, support, and guide solutions across data ... AI Platform Enablement & Configuration * Develop a deep understanding of enterprise AI platforms ...

Own the strategy and execution of the Data, Analytics and AI Practice. * Build the Practice: Stand up and scale offerings, capabilities, and team from the ground up. * Drive Growth: Deliver revenue ...

Own the strategy and execution of the Data, Analytics and AI Practice. * Build the Practice: Stand up and scale offerings, capabilities, and team from the ground up. * Drive Growth: Deliver revenue ...

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

... support analytics and decision-making, and providing client-facing consulting services that ... Provide executive-level advisory services on AI adoption and data modernization, tailoring ...

AI/ML and Data Engineer

Southfield, MI

$104K - $125K/yr

... support analytics and decision-making, and providing client-facing consulting services that ... Provide executive-level advisory services on AI adoption and data modernization, tailoring ...

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Ai Data Analytics information

See Michigan salary details

$21

$47

$82

How much do ai data analytics jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for ai data analytics in Michigan is $47.72, according to ZipRecruiter salary data. Most workers in this role earn between $38.37 and $54.04 per hour, depending on experience, location, and employer.

What is AI data analytics?

AI Data Analytics refers to the use of artificial intelligence technologies to analyze and interpret large volumes of data. By leveraging machine learning algorithms, natural language processing, and other AI methods, professionals in this field can uncover patterns, make predictions, and drive data-driven decision-making. AI Data Analytics is widely used across industries to optimize operations, improve customer experiences, and gain competitive insights. The role typically involves working with big data platforms, developing models, and communicating findings to stakeholders.

What skills and qualifications are needed to thrive as an AI data analyst?

To thrive as an AI Data Analyst, you need a strong background in statistics, data analysis, and machine learning, typically supported by a degree in computer science, mathematics, or a related field. Proficiency with tools such as Python, R, SQL, and data visualization platforms like Tableau, along with knowledge of AI frameworks such as TensorFlow or PyTorch, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and present actionable insights to stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the impact of AI initiatives within organizations.

How does an AI data analytics professional typically collaborate with cross-functional teams within an organization?

AI Data Analytics professionals frequently work alongside departments such as marketing, operations, IT, and product development to interpret complex datasets and provide actionable insights. Collaboration often involves translating business needs into data-driven solutions, communicating findings in accessible terms, and ensuring that analytics projects align with organizational goals. Effective teamwork and clear communication are crucial, as analytics professionals must bridge the gap between technical data analysis and practical business application.

What is the difference between Ai Data Analytics vs Data Scientist?

AspectAi Data AnalyticsData Scientist
Required CredentialsBachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analyticsBachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred
Work EnvironmentTech companies, finance, healthcare; focus on AI-driven data analysisResearch labs, tech firms, finance; focus on data modeling and insights
Employer & Industry UsageUsed in industries leveraging AI for predictive analytics and automationUsed 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.

Is data analysis a good career with AI?

A career in AI Data Analytics is considered promising due to the increasing demand for data-driven decision making and AI integration across industries. Professionals in this field need strong skills in data manipulation, statistical analysis, and tools like Python or R. The role offers growth opportunities, competitive salaries, and the chance to work on innovative technologies.

What does an AI data analyst do?

An AI data analyst collects, processes, and analyzes large datasets to extract insights that inform business decisions. They use tools like Python, R, and machine learning algorithms to identify patterns and trends, often working closely with data engineers and data scientists to develop predictive models and automate data workflows.

What are popular job titles related to Ai Data Analytics jobs in Michigan?

For Ai Data Analytics jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Ai Data Analytics jobs in Michigan look for?

The top searched job categories for Ai Data Analytics jobs in Michigan are:

What cities in Michigan are hiring for Ai Data Analytics jobs?

Cities in Michigan with the most Ai Data Analytics job openings:

Infographic showing various Ai Data Analytics job openings in Michigan as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $99,251 per year, or $47.7 per hour.

$113K - $136K/yr

Full-time

Re-posted 12 days ago


Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME

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About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

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