Manager Analytics – CM Analytics Transformation

Caterpillar•Chicago, IL

1d•Onsite

About The Position

Career Area: Technology, Digital and Data 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. Cat® Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital and analytics solutions for our customers and dealers. We’ve created an inclusive environment for you to explore your passions, make an impact and do the work that really matters. With over 1.5M connected assets worldwide, our business and in the industries, we serve, data is generated continuously by Cat® equipment using the latest technology, advanced analytics, telematics and AI capabilities to help our customers build a better world. Job Summary: The Condition Monitoring (CM) Analytics Team within Cat Digital’s Analytics and Applied AI organization seeks a talented and motivated Analytics Manager to lead the CM Analytics Transformation team. This hands-on manager leads a team of data scientists to develop, production deploy, and support next-generation analytics to transform Condition Monitoring Advisor (CMA) workflow in the Cat Foresight CM application, including scalable failure modeling approaches, evidence and context clustering, CMA persona modeling, and closed-loop learning on CMA behavior to provide high-confidence asset insights and predictive maintenance recommendations.

Requirements

Business Statistics: Knowledge of statistical tools, processes, and practices to evaluate results and guide decision making
Products and Services: Knowledge of major products and services and product and service groups; ability to apply knowledge of product and service appropriately to diverse situations.
Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of both technical and organizational problems, and to create alternative solutions that resolve these problems.
Innovation: Ability to create and develop new ideas for answers to business and technical problems; identify, develop, and evaluate high value opportunities to improve performance and deliver business value for CM Transformation
Machine Learning: Strong knowledge of modern ML/AI methods for supervised and unsupervised learning, recommender systems, and agentic approaches to transforming IOT event/diagnostic/timeseries data, inspections, fluids analyses, asset context, service data, etc. into comprehensive asset-level predictive maintenance undefined

Nice To Haves

B.S. in data science, applied mathematics/statistics, engineering, or related technical field (advanced degree desirable)
Typically 12 years work experience in technical and leadership roles, including 8 years in data science, analytics, AI, engineering, or similar role, and 4 years leadership experience over analytics, digital, and/or software development teams
Expertise in python ML stacks and modern AI frameworks
Experience developing digital solutions in the IOT / condition monitoring space
Familiarity with Caterpillar products, applications, data, and digital ecosystem a strong plus
Passion and skills for recruiting, interviewing, talent development, and the care and feeding of teams

Responsibilities

Build, manage, and execute the CM Analytics Transformation portfolio collaborating with commercial, digital product, and engineering / R&D / ML & AI Ops teams.
Identify assets requiring intervention; assemble relevant evidence and context; generate high-quality, persuasive, specific, actionable recommendations.
Drive innovation and execution to deliver on commitments.
Set, adjust, and communicate priorities; develop contingency plans; manage resource loading; monitor program results.
Supervise and provide hands-on technical guidance to a team of 8-12 data scientists, accountable for their success and responsible for hiring, performance management, technical and career coaching.
Foster a culture of customer focus and collaboration, cultivating a sense of urgency and also of psychological safety.