Career Area:

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.

Key Responsibilities:

• Develop predictive maintenance, anomaly detection, and Remaining Useful Life (RUL) algorithms for gas engines.

• Analyze large-scale machine and time-series data to identify failure patterns and degradation mechanisms.

• Design, develop, validate, and continuously improve machine learning models and analytics solutions.

• Translate engine failure mechanisms into software requirements and analytics models.

• Collaborate with service engineers, product experts across divisions as well as external software development partners.

Requirements:

• Degree in Data Science, Computer Science or a related field ideally with knowledge of gas engine and failure analysis.

• Strong knowledge in Python (e.g., pandas, NumPy), SQL, machine learning and AI methods and expertise in time series analysis and machine learning model development

• Experienced working with large-scale data platforms and cloud environments (e.g., Azure, AWS)

• Ideally experienced in using CAT ACE / ACEint and CAT Foresight.

• Excellent analytical and communication skills, with the ability to work effectively in cross-functional teams

• High level of self-motivation, ownership, and ability to work independently

Posting Dates:

Caterpillar is an Equal Opportunity Employer.  Qualified applicants of any age are encouraged to apply

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