Senior Manager - Connectivity Data Analytics

Caterpillar Caterpillar · Industrial · Mossville, IL

Senior Manager role focused on driving data- and AI-enabled engineering transformation within Caterpillar's Connectivity organization. The role leads the strategy, delivery, and adoption of analytics, automation, and AI solutions to improve connectivity quality, engineering efficiency, system reliability, and customer outcomes. It involves people leadership, technical judgment, and enterprise change leadership, translating connectivity data into insights and scalable AI capabilities. Key responsibilities include defining strategy, leading development of data products, applying AI/ML and GenAI to engineering workflows (validation, fault detection, predictive insights, AI-assisted diagnostics), managing a portfolio of initiatives, and fostering stakeholder partnerships and change management. The role also involves building and leading a high-performing team.

What you'd actually do

  1. Define and own the Connectivity Analytics, aligned to Connectivity strategy, Digital Data & AI standards, and Helios platform capabilities
  2. Lead development and governance of connectivity data products built on Helios (semantic models, curated datasets, APIs, dashboards)
  3. Apply AI/ML and GenAI capabilities to connectivity engineering workflows, including: Validation and test automation, Fault, anomaly, and pattern detection, Predictive insights for reliability and service readiness, AI-assisted documentation, diagnostics, and root-cause analysis
  4. Manage a portfolio of analytics and AI initiatives across Connectivity Quality, Validation, Engineering Efficiency, and Service Solutions
  5. Build and lead a high-performing team spanning analytics, data engineering, analytics engineering, and applied AI

Skills

Required

  • Bachelor’s degree in Engineering, Computer Science, Data/Analytics, or related quantitative field (or equivalent experience)
  • Strong experience leading analytics and/or AI initiatives in complex engineering or technology environments
  • Demonstrated people leadership experience managing managers and technical professionals
  • Proven ability to translate ambiguous engineering problems into scalable data and AI solutions

Nice to have

  • Advanced degree preferred
  • Experience with connected systems, telematics, IoT data, or embedded/on‑machine plus cloud ecosystems
  • Hands‑on familiarity with modern data platforms, analytics tooling, and ML/AI delivery patterns
  • Advanced analytical thinking and problem structuring
  • Connectivity, telemetry, or large‑scale operational data understanding
  • Data modeling, KPI design, and analytics product ownership
  • Working knowledge of ML/AI and GenAI application patterns
  • Understanding of MLOps/LLMOps concepts (monitoring, drift, retraining)
  • Enterprise transformation and change leadership
  • Executive communication and data storytelling
  • Cross‑functional influence without direct authority
  • Strong judgment balancing speed, rigor, and risk

What the JD emphasized

  • AI-enabled engineering transformation
  • Connectivity organization
  • Cat® Helios
  • connectivity quality
  • engineering efficiency
  • system reliability
  • customer outcomes
  • connectivity data products
  • AI/ML and GenAI capabilities
  • pilot → production → sustained adoption
  • responsible AI
  • model evaluation
  • monitoring
  • retraining
  • access control
  • audit readiness
  • trusted analytics and AI advisor
  • data-driven decisions
  • automation
  • reusability
  • measurable outcomes
  • analytics and/or AI initiatives
  • connected systems, telematics, IoT data, or embedded/on‑machine plus cloud ecosystems
  • ML/AI delivery patterns
  • MLOps/LLMOps concepts

Other signals

  • AI/ML and GenAI capabilities to connectivity engineering workflows
  • pilot -> production -> sustained adoption
  • responsible AI, model evaluation, monitoring, retraining, access control, and audit readiness