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Manufacturing Data Analytics Jobs in Howell, MI (NOW HIRING)

Knowledge of ERP and Manufacturing Execution Systems (MES) * Data Analysis and Reporting * Project Management * Strong Communication and Collaboration Skills * IT Security and Compliance Knowledge

New

Manufacturing Controls Engineer

Novi, MI · On-site

$79K - $93K/yr

Support manufacturing execution systems (MES), production traceability, and automation interfaces ... Analyze equipment performance data to identify automation improvements and efficiency gains

Manufacturing Engineer

Plymouth, MI · On-site

$69K - $89K/yr

Including TDP (Technical Data Package), Bill of Material, Process Flow / Routings, Floor Layouts ... Excellent organizational, analytical, interpersonal and communication skills. * Ability to work in ...

Analyze production data and participate in root cause investigations. * Implement corrective actions and support Lean Manufacturing initiatives to improve overall equipment effectiveness (OEE ...

Analyze production data and participate in root cause investigations. * Implement corrective actions and support Lean Manufacturing initiatives to improve overall equipment effectiveness (OEE ...

Engineer - Warranty and Reliability

Novi, MI · On-site

$96K - $121K/yr

... manufacturing, and suppliers. Essential Duties and Responsibilities: Warranty Analytics & Reporting * Analyze warranty claims, returns (RMA), and field performance data to identify trends and ...

Showing results 21-40

Manufacturing Data Analytics information

What is manufacturing data analytics?

Manufacturing data analytics refers to the use of data analysis tools and techniques to collect, interpret, and leverage data generated during manufacturing processes. This approach helps companies identify inefficiencies, predict equipment failures, optimize production, and improve product quality. By analyzing data from sensors, machines, and other sources, manufacturers can make informed decisions that boost productivity and reduce costs. Overall, manufacturing data analytics is key for driving digital transformation and competitiveness in the manufacturing industry.

How do manufacturing data analytics professionals collaborate with production and engineering teams to drive process improvements?

Manufacturing Data Analytics professionals work closely with production and engineering teams by analyzing process data, identifying inefficiencies, and presenting actionable insights. They often participate in cross-functional meetings, where they translate complex data findings into practical recommendations for process optimization, quality improvement, or cost reduction. Effective communication and a collaborative approach are essential, as these professionals must understand operational challenges and ensure data-driven solutions are feasible and aligned with business goals.

What are the key skills and qualifications needed to thrive in manufacturing data analytics, and why are they important?

To thrive in Manufacturing Data Analytics, you need a strong background in statistics, data analysis, and manufacturing processes, often supported by a degree in engineering, data science, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), programming languages like Python or R, and ERP/MES systems is typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex insights clearly are essential soft skills. These competencies enable professionals to drive process improvements, optimize production, and support data-driven decision-making in manufacturing environments.

What is the difference between Manufacturing Data Analytics vs Manufacturing Data Engineer?

AspectManufacturing Data AnalyticsManufacturing Data Engineer
Primary FocusAnalyzing manufacturing data to improve processes and decision-makingDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsData analysis, statistical skills, knowledge of manufacturing processes, often with certifications in data analytics or related fieldsData engineering, programming (Python, SQL), cloud platforms, database management
Work EnvironmentCollaborates with manufacturing teams, data teams, and managementWorks with IT, data teams, and software engineers to develop data systems
Industry UsageUsed across manufacturing sectors for process optimizationSupports manufacturing analytics by providing data infrastructure

Manufacturing Data Analytics focuses on interpreting manufacturing data to enhance operations, while Manufacturing Data Engineers develop and maintain the data systems that enable such analysis. Both roles are essential in manufacturing data-driven strategies but differ in their core responsibilities and skill sets.

What job categories do people searching Manufacturing Data Analytics jobs in Howell, MI look for?

The top searched job categories for Manufacturing Data Analytics jobs in Howell, MI are:

Infographic showing various Manufacturing Data Analytics job openings in Howell, MI as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Sr IT Director- Data Analytics & AI, AFM, Commercial, Engineering & EV

Dana Corporation

Novi, MI • On-site

Other

Posted yesterday

New


Dana Incorporated rating

5.9

Company rating: 5.9 out of 10

Based on 79 frontline employees who took The Breakroom Quiz

450th of 490 rated machine equipment manufacturers


Job description

Job Purpose
The Sr IT Director- Data Analytics & AI, AFM, Commercial, Engineering & EV is a senior leadership role responsible for defining and executing the company's enterprise-wide data strategy, with a strong focus on Master Data Management (MDM), data governance, and AI-driven transformation across Aftermarket (AFM) and Commercial domains.
This role leads the end-to-end data value chain-from master data integrity and governance to advanced analytics and AI-ensuring that enterprise data is trusted, unified, and actionable. The Sr. Director will partner closely with business, digital, and engineering leaders to embed data and AI into core commercial and operational processes, driving measurable outcomes in revenue growth, customer experience, and operational performance.
Job Duties and Responsibilities
Enterprise Data & AI Strategy Leadership
Define and lead the enterprise data strategy, anchored in MDM, data governance, analytics, and AI, aligned to AFM and Commercial growth priorities.
Establish a multi-year roadmap spanning master data, data platforms, analytics, and AI/GenAI capabilities.
Act as a strategic advisor to executive leadership, shaping how data and AI drive competitive advantage, revenue, and operational excellence.
Build and lead a high-performing global organization across MDM, data engineering, governance, analytics, and data science.
Master Data Management (MDM) & Data Governance
Own and institutionalize enterprise MDM strategy and platforms across core domains (Customer, Product, Supplier, Pricing, Assets).
Establish data ownership, stewardship models, and domain accountability across AFM and Commercial.
Drive data standardization, harmonization, and lifecycle management to enable consistent reporting and AI readiness.
Lead enterprise-wide data governance frameworks, including policies, quality management, lineage, and metadata.
Ensure compliance with regulatory, privacy, cybersecurity, and intellectual property standards.
Define and track data quality KPIs and drive continuous improvement across business domains.
Data Platforms & Architecture
Own the strategy and evolution of modern data platforms, including lakehouse architectures, real-time data pipelines, and semantic data layers.
Ensure platforms are AI-ready, scalable, secure, and optimized for cost and performance.
Partner with Enterprise Architecture and Cybersecurity to enforce standards, data models, and integration patterns.
Enable seamless integration of ERP, CRM, supply chain, and engineering data into unified data products.
Analytics, AI & Advanced Capabilities
Define and scale a portfolio of high-impact analytics and AI use cases, including:
o Commercial performance, pricing, and margin optimization
o Aftermarket demand forecasting and parts optimization
o Customer insights and segmentation
o Predictive maintenance and service optimization
o AI-enabled anomaly detection and operational intelligence
o Generative AI for commercial insights, automation, and decision support
Lead the end-to-end AI lifecycle (ideation to production) with strong MLOps and governance practices.
Establish a product-based data & analytics operating model, delivering reusable, scalable data products and AI capabilities.
AFM & Commercial Business Alignment
Partner with AFM and Commercial leaders to translate business strategy into data, MDM, and AI solutions.
Ensure master and transactional data enable core commercial processes including quoting, pricing, forecasting, and customer engagement.
Drive use of data and AI to enhance revenue growth, profitability, and customer experience.
Act as the primary data and AI leader for AFM and Commercial transformation initiatives.
Education and Qualifications
Required
Bachelor's degree in Computer Science, Engineering, Data, or related field (Master's preferred).
12-15+ years of experience in enterprise data, MDM, analytics, and AI leadership roles.
Proven track record leading enterprise-scale MDM and data transformation programs.
Deep expertise in data governance, master data domains, and modern data architectures.
Experience delivering AI/analytics solutions with measurable commercial impact.
Strong leadership experience managing global, cross-functional teams and transformation programs.
Preferred
Hands-on experience with MDM tools/platforms, data quality frameworks, and metadata management.
Familiarity with AI/ML, MLOps, and GenAI applications in commercial or industrial settings.
Experience in manufacturing, aftermarket, or asset-intensive industries.
Exposure to OT/IT convergence and engineering data ecosystems.
Strong executive presence with ability to influence at C-suite level.
Measures of Success
Business value delivered through data, MDM, and AI initiatives (revenue, margin, cost, productivity)
Enterprise data quality, consistency, and governance maturity
Adoption and impact of analytics and AI in AFM and Commercial operations
Speed and scalability of data product and AI delivery
Effectiveness of MDM in enabling enterprise-wide insights and processes
Join our team of 28,000 problem solvers who are fostering a culture of innovation by leveraging the diverse perspectives of our global team. We believe in facing challenges head-on by finding opportunity and uncovering possibility, where roadblocks and barriers become targets instead of obstacles. We are One Dana with limitless opportunity.
Our Values
  • Value Others
  • Inspire Innovation
  • Grow Responsibly
  • Win Together

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