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.
Responsibilities :
In this role, you will be exposed to Caterpillar’s engine systems products, technologies, processes, and services, which you will use to :
- work with time-series data from sensors and aggregate / unstructured data from other sources
- develop physics-based / rule-based / data-driven algorithms for condition monitoring
- develop, test and demonstrate machine learning models for failure / anomaly detection
- communicate results to customers, suppliers, team members, and other business units
- capture the knowledge generated and document for reference
Requirements :
Sound understanding of engineering fundamentalsKnowledge of Internal Combustion engines & systems (Thermodynamics)Coding experience in any programming language, preferably PythonExcellent Verbal and Written Communication SkillsAbility to engage with in-person interactions with team members & also able to work independentlyQualifications & Experience (essential) :
Bachelor’s degree in Mechanical / Automotive / Electrical / Electronics engg or equivalentExperience of 3 to 5 years in design, analysis, simulation, data analytics or related fieldSkills : Python, SQLTop candidates will also have :
Master’s degree in engineeringBasic understanding of statistics / signal processingExperience in IoT / sensor data analyticsExperience with databases (Snowflake, Oracle, MySQL etc)Hands-on experience in version control (Git / DevOps)Data Visualization experience – Power BI, Tableau etcHave worked on the python modules – pandas, scikit learn, numpy, scipy, plotly etc