Data & AI Specialist
Cat
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- Why do you want to join Cat?
- What is your experience with Generative AI? Tell me one thing you learned the hard way.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
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Practise the Data & AI Specialist at Cat interview free →Career Area: Engineering Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Position Summary The Data & AI Specialist is responsible for developing and enabling the factory's data and AI capabilities through data governance, data architecture, analytics platforms, and AI solution deployment. This role serves as the subject matter expert for manufacturing data and AI technologies, driving the establishment of data standards, data quality systems, digital platforms, and AI applications that support operational excellence and smart manufacturing transformation. The position works closely with Operations, Engineering, Quality, Supply Chain, IT, and business stakeholders to unlock business value from data and AI. Key Responsibilities Data Governance & Data Standards Establish and maintain the factory data governance framework, standards, and best practices. Define and manage: Data quality rules Data quality monitoring KPIs Data ownership and stewardship processes Data lifecycle management standards Develop and maintain Data Owner and Data Steward responsibility matrices. Conduct regular data quality assessments and drive corrective actions. Ensure consistency, accuracy, completeness, and reliability of critical business data. Data Architecture & Master Data Management Design and maintain manufacturing data models and data architecture. Develop and govern: Master data standards Data dictionary Metadata management Naming conventions Data flow documentation Establish common KPI definitions and business metric standards across functions. Support enterprise-wide master data governance initiatives. Data Collection & Integration Drive structured digital data collection at the source to reduce manual spreadsheets and offline records. Design and implement automated data acquisition solutions. Integrate data from: ERP systems MES systems Quality systems Supply chain systems Production equipment IoT devices Define data interface standards and integration requirements. Support development of scalable data pipelines and digital platforms. Analytics Platform & Decision Support Support development and optimization of data warehouse and analytics solutions. Build and maintain data models that enable operational and management reporting. Develop dashboards and visualization solutions using enterprise BI platforms. Translate business requirements into meaningful insights and performance indicators. Enable self-service analytics capabilities for business users. AI Strategy & Use Case Development Support development of factory AI roadmap aligned with smart manufacturing and business strategies. Identify, evaluate, and prioritize high-value AI use cases. Establish processes for: AI opportunity assessment Feasibility analysis Solution validation Benefits tracking Monitor emerging AI technologies and evaluate business applicability. AI Solution Deployment Lead and support implementation of manufacturing AI applications, including: Computer Vision Automated Quality Inspection Predictive Maintenance Process Optimization Production Scheduling Optimization Quality Analytics Root Cause Analysis Safety Monitoring Energy Management Work closely with business teams, IT partners, and vendors to ensure successful deployment and adoption. Generative AI & Productivity Enablement Drive GenAI adoption across the factory through: Knowledge management solutions Enterprise knowledge bases Digital assistants and AI agents Copilot enablement Workflow automation Power Platform applications Office productivity automation Promote practical GenAI use cases that improve employee productivity and business efficiency. AI Governance & Risk Management Support establishment of AI governance processes and standards. Monitor AI solution performance and business outcomes. Assist in managing: Model lifecycle Compliance requirements Data privacy Risk controls AI usage guidelines Ensure responsible and sustainable AI implementation. Data Security & Compliance Support implementation of data security and access control policies. Ensure compliance with corporate data governance requirements. Define data retention and archival standards. Protect sensitive business and operational information. Capability Building & Training Promote data-driven decision making across the factory. Develop and deliver training programs on: Data literacy Analytics AI fundamentals GenAI tools Citizen development Power Platform Coach business teams on data and AI best practices. Qualifications Education Bachelor's degree or higher in: Data Science Computer Science Information Systems Industrial Engineering Manufacturing Engineering Artificial Intelligence Statistics Related disciplines Experience 5+ years of experience in data analytics, data engineering, digital transformation, AI, or manufacturing systems. Experience implementing data governance programs. Experience with manufacturing data environments preferred. Experience delivering analytics or AI solutions in industrial settings preferred. Technical Skills Strong experience in: Data Governance Master Data Management Data Modeling SQL Data Warehousing ETL / ELT Processes Power BI Azure Data Platform AI / Machine Learning Fundamentals Generative AI Technologies Microsoft Copilot Power Platform Knowledge of manufacturing systems: SAP / ERP MES IoT Platforms SCADA Historian Systems Preferred Qualifications CDMP (Certified Data Management Professional) DAMA Data Governance Knowledge Microsoft Fabric, Azure AI, or equivalent cloud certifications Experience in Industry 4.0 or Smart Manufacturing programs Experience deploying AI solutions in manufacturing environments This position requires the candidate to work a 5-day-a-week schedule in the office. About Caterpillar Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. For nearly 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed. This position requires working onsite five days a week. Visa Sponsorship is not available for this position. Posting Dates: 十月 8, 2026 - 十月 21, 2026 Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply Not ready to apply? Join our Talent Community .
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Listed on workday · posted 2026-11-09. ApplySarthi collects openings and links to application pages; the role is advertised by Cat, not by us.