Caterpillar Inc.

Research Analyst

• Leverage new and existing customer insights tracking survey data, transactional survey data and primary market research to help CAT business units and CAT dealers identify what experiences and key actions will drive long term loyalty and increased share of wallet across all customer touch points.
• Drive continuous improvements in survey content, focus efforts on the key drivers of loyalty, and increase enterprise awareness through training and communication efforts.
• Maintains accountability with True Voice Program (TVP) dealer onboarding goals and deliverables.
• Communicates with and coordinates dealer and internal support resources to troubleshoot issues with survey alerts and data dashboards.
• Analyzes and critiques post program results to determine if goals were met; recommends alternative action plans.
• Works as a team with dealer and market research consultant to gain maximum benefit from company resources.
• Directs data quality review and audit processes.
• Other duties as assigned by Caterpillar management from time-to-time.

Market Research Consultant

Business Analyst

• Caterpillar is looking for a Digital Business Analyst to join the Cat Digital Subscription and Billing Services digital product management team
• Maximize the value of the product through strong partnership with product owners, business partners and engineering, utilizing deep domain expertise to create and maintain a detailed product backlog
• Ensure we have deep understanding of users and their processes (triggers, steps, roles, outcomes)
• Product manage components of complex, cross product initiatives with high value to the organization, through backlog planning, scope validation, impact analysis, functional requirements identification and documentation of epics and features
• Build tight collaboration and understanding of stakeholder needs and business goals across impacted products
• Lead detailed definition of major experience elements - covering the logic, structure, skeleton, and relationships of how an experience should come together across functions/domains, including facilitation of wireframe creation
• Define user acceptance test criteria as direct input to testing plans, conduct and/or coordinate business acceptance testing and sign-off to ensure epic and features are delivered according to agreed-upon business expectations

Digital Business Analyst I, Subscription & Billing Services

Field Engineer

• Support start-up and commissioning for power generation sites including gas engines, control systems, generators, and auxiliary equipment.
• Troubleshoot, diagnose, and resolve technical issues on-site and remotely, developing corrective actions and communicating technical findings with sense of urgency to customers, dealers, and internal stakeholders.
• Provide deep technical support to customers and dealers through training sessions, workshops, and field support.
• Support continuous improvement projects (CPI) and new product introductions (NPI) activities through root cause investigations at customer sites, including documentation and evaluation of field experience to drive mitigation actions, product development, and updates to technical documentation and safety standards.

Product Service Engineer

Business Intelligence Developer

• Define adoption and behavioral success frameworks, including leading and lagging indicators and measurement cadence.
• Analyze usage patterns, engagement signals, and behavioral trends to identify drivers of adoption and areas of friction.
• Integrate qualitative feedback (surveys, interviews) with quantitative metrics to provide actionable insights.
• Design and build adoption dashboards using Power BI, Tableau, or similar BI tools.
• Partner with data and engineering teams to model adoption datasets in Snowflake or comparable data platforms.
• Create mock‑up dashboards (e.g., Figma) to align stakeholders on metric intent and visualization approach.
• Document data sources, joins, calculations, and metric definitions to ensure reporting consistency and trust.
• Establish governance for adoption reporting, including metric definitions, refresh cadence, ownership, and data quality checks.
• Ensure accurate, timely, and auditable visibility of adoption metrics for internal teams and dealer audiences.
• Create repeatable documentation and standards to support scalable reporting.
• Partner closely with Product, DACS, Dealers, Customer Support, and Industry Partners to align on adoption insights and priorities.
• Research industry trends and best practices in digital and AI adoption measurement and incorporate learnings into internal approaches.
• Communicate findings clearly to technical and non‑technical audiences.

Lead Business Intelligence Analyst

Customer Support

• Own the end-to-end intake and synthesis of Voice of Customer (VoC) and Voice of Dealer (VoD) feedback for the Cat AI Assistant and related digital experiences.
• Collect and consolidate VoC/VoD feedback from multiple channels (e.g., support cases, dealer communications, research studies, field inputs, stakeholder interviews, surveys).
• Establish a repeatable approach to categorize feedback into themes such as usability, performance, feature gaps, trust, and workflows.
• Distill high-volume inputs into concise insights that articulate what is happening, who is impacted, why it matters, and recommended next actions.
• Translate customer and dealer feedback into high-quality work items (problem statements, user stories, acceptance criteria, expected outcomes) to support product and engineering teams.
• Partner with product managers to inform prioritization decisions by providing context, impact, and urgency based on real customer experience signals.
• Track feedback-driven items through delivery and help close the loop by communicating outcomes back to stakeholders.
• Partner with Customer Support and field-facing teams to improve feedback quality, consistency, and escalation pathways.
• Collaborate with researchers, other product partners, and internal divisions to align on insights and reduce duplication of effort.
• Identify, document, and report design, reliability, and usability issues affecting customer and dealer experiences.

Digital Customer Experience Specialist

Data Scientist

• Design and execute AI experiments across the full model lifecycle: hypothesis formulation, data preparation, model development, evaluation, and iteration, maintaining research rigor in an ambiguous, fast-moving environment.
• Develop, fine-tune, and benchmark LLMs and multimodal AI models (text, vision, speech), including systematic evaluation of quality, latency, cost, and safety tradeoffs across model variants and providers.
• Explore and optimize knowledge retrieval systems (RAG pipelines, vector databases, hybrid search) and agentic workflows, ensuring relevance, accuracy, and scalability for enterprise use cases.
• Lead data preparation workstreams for model training, fine-tuning, and validation, including dataset curation, labeling strategy, synthetic data generation, and quality assurance.
• Instrument AI systems for observability and reproducibility using experiment tracking frameworks (e.g., Langfuse, MLflow), maintaining clear documentation of model versions, evaluation datasets, and performance baselines.
• Translate research findings into production-ready prototypes, collaborating with Engineering and Product teams to define technical requirements, integration paths, and deployment readiness criteria.
• Evaluate emerging AI capabilities and tools (open-source and commercial), providing structured assessments and recommendations to inform the team's technology strategy.
• Mentor and coach junior Data Scientists, establishing best practices for experimentation, model evaluation, and responsible AI development across the team.
• Communicate insights and results to technical and non-technical stakeholders, including product managers, engineers, and senior leadership, with clarity and business impact framing.

Senior Data Scientist – Artificial Intelligence R&D

• Stay current with emerging AI research by conducting ongoing literature reviews across core AI workstreams such as speech/voice, vision, multimodal systems, retrieval, and autonomous agents, and actively apply relevant innovations to Cat Digital’s AI R&D portfolio.
• Assess and compare academic and industry advancements to guide architecture choices, experimentation strategy, and production‑readiness decisions.
• Synthesize research findings into practical, enterprise‑relevant insights that influence prototyping priorities and long‑term AI strategy.
• Lead hands‑on experimentation and development of advanced machine learning and generative AI solutions, including LLMs, multimodal models (text, vision, speech), retrieval ‑ augmented generation (RAG), agents, and simulation/digital ‑ twin use cases.
• Design, build, and curate high ‑ quality datasets for training, fine ‑ tuning, validation, and evaluation of AI models at scale.
• Define and execute rigorous model evaluation strategies, including benchmarking model quality, accuracy, latency, cost, robustness, and safety tradeoffs.
• Drive rapid prototyping and POC development with a strong focus on reproducibility, experiment tracking, and observability to enable informed technical decision ‑ making.
• Research, compare, and optimize model architectures, algorithms, and AI system designs to improve performance, scalability, and enterprise readiness.
• Partner with Product and Engineering teams to translate research outcomes and prototypes into production ‑ ready capabilities, including defining technical requirements and success metrics.
• Communicate complex technical findings and insights clearly to both technical and non ‑ technical stakeholders, influencing roadmap and investment decisions.

Lead Data Scientist – Artificial Intelligence R&D

Learning and Development

• Designing and delivering comprehensive learning programs and assets tailored to critical dealer digital job roles.
• Collaborating with digital product teams and actively seeking feedback from Digital Adoption Representatives (DARs) and Product Adoption Consultants (PACs) to create learning resources that are relevant, impactful, and meet evolving dealer needs.
• Measuring the effectiveness of learning assets and programs by gathering performance data, monitoring ROI, and implementing improvements to maximize digital competency and adoption.
• Maintaining and updating learning materials to stay compliant with organizational policies and reflect the latest digital solutions and practices.
• Evaluating and implementing new instructional methods, technologies, and content options—leveraging proven adult learning techniques and creative approaches to enhance learner engagement and outcomes.
• Consulting with business partners to assess digital learning requirements and ensure programs support both organizational strategy and dealer success.

Digital Learning Consultant

Manager

• Provide leadership and oversight for IT service delivery within a complex enterprise environment.
• Monitor service levels, manage vendor performance, and identify opportunities for efficiency improvement.
• Coordinate with other internal and outsourced service management functions on service issues and problem management.
• Monitor, review and communicate on actual and expected service levels.
• Conduct assessments, determine process gaps and suggest improvements.
• Implement service and process improvements within the allotted budget.

IT Service Level Manager I

Operations

• Provide executive leadership across manufacturing and extended supply chain operations, ensuring end‑to‑end alignment from suppliers through fabrication, assembly, and delivery to customers.
• Lead the scaling of advanced manufacturing capabilities, including automation, digital manufacturing, and smart factory technologies to improve safety, quality, cost, and delivery.
• Lead, develop, and performance‑manage senior manufacturing leaders and operations teams; build a strong leadership bench and high‑performance culture at scale.
• Drive a world‑class safety culture, ensuring regulatory compliance and proactive risk mitigation across all sites.
• Own operational performance, including production, quality, cost, delivery, and capacity management, using data‑driven systems and disciplined operating rhythms.
• Partner closely with engineering, product, sales, and business leadership to align manufacturing strategy with product roadmaps, customer demand, and long‑term business objectives.
• Lead continuous improvement and transformation initiatives, including Lean manufacturing, advanced manufacturing technologies, and operational excellence programs across the division.
• Enable flexibility and scalability in a complex, low‑volume / high‑mix environment while maintaining durability and quality standards for highly engineered equipment.

Vice President – Manufacturing Operations

• Lead the global Orders Operations Support team.
• Ensure business continuity, effective issue management, drive continuous improvement, solution delivery, and system performance.
• Translate business requirements into process and functional specifications.
• Oversee and execute order operations systems’ testing, validation, change management activities, training and documentation.
• Ensure governance, compliance, and production readiness of existing and new products and processes, managing transitions from development to production.

Order Operations Support Supervisor

Systems Engineer

• Documenting architecture specifications, software design description, verification plans, test cases, operating procedures, and safety procedures.
• Utilizing appropriate tools to debug, test and maintain software and hardware systems; completing the verification and validation process.
• Participating in design and development of application software and algorithms for emerging platforms.
• Applying engineering judgment to evaluate design tradeoffs, integration risks, and verification approaches.
• Working independently on moderately complex system integration problems within established product architectures.
• Providing technical guidance to less experienced engineers without formal leadership responsibility.

Control Systems Engineering Specialist

Program Manager

• Builds, maintains, and manages the program schedule and day-to-day activities for the 2030 Strategy deliverables for Condition Monitoring, Inspections, and CVA Maintenance & Repair Management.
• Develops contingency plans for potential risks.
• Evaluates and manages deliverables and resource loading to ensure that expectations are achievable, developed, and met.
• Monitors program results for significant deviations.
• Ensures adherence to quality standards and processes per the Cat® Digital operating model.
• Collaborates with all Cat® Foresight & Cat® Inspect product managers in the development and execution of program plans.
• Communicates ongoing governance & risks for program plans with internal and external stakeholders.

Principal Digital Program Manager – Cat Foresight

• Support our End-to-End Built-In Quality by developing defect detection and driving defect reduction, speeding field recovery, and improving fleet reliability.
• Provide hands‑on leadership supporting commissioning and complex field deployments.
• Improve serviceability and repair procedures to support long‑term fleet growth.
• Evaluate the results to identify functional deficiencies.
• Capture and share lessons learned and Best Practices from a problem-solving effort.
• Advocate on behalf of the dealer and customer and drive effective solutions to technical challenges.
• Ensure seamless collaboration and alignment with internal and external teams.
• Maintain strong internal and external relationships via delivery of commitments, open communication, and ongoing feedback.
• Resolve customer complaints or complex problems by troubleshooting root causes and organizing appropriate subject matter experts, then leading problem resolution and field validation efforts with appropriate sense of urgency.
• Write technical specifications and instructions to ensure effective product service that results in a high level of product reliability and performance.

Senior Product Service Engineer

Software Engineer

• Solve challenging problems for mobile off-road machines.
• Participate in design and development of high-quality software and algorithms to solve our customer needs.
• Document architecture specifications, software design, verification plans, test cases, operating procedures, and safety procedures.
• Work with application teams to collect and analyze data on customer experience with robotic and manned platforms.
• Use appropriate tools to debug, test and maintain software and assist in the verification and validation process.