Embedded Prod Analytics Engineer

**Career Area**:Engineering**:
For Caterpillar, digital means using technology to extract data from our machines and engines and transform it into valuable recommendations or “insights,” to help customers make better, more informed decisions and help Caterpillar make robust products with the lowest total ownership cost. Our products generate and process large amounts of data from sensors, on-board models, and control algorithms in real-time creating real-world machine usage information. Additionally, data is generated through numerous quality systems to provide information about internal and external quality defects and external failures. This data represents a rich body of machine information that is highly useful for product development and product improvement once mined, aggregated, and analyzed for actionable insight using embedded product analytics.

**Job Purpose**:
Embedded Product Analytics uses quantitative methods to solve problems for internal and external Caterpillar customers by using data from sensors, on-board models, control algorithms, internal quality systems, and external quality systems. Engineer 2 - Embedded Product Analytics contributes to this mission by providing basic quantitative analysis, communication, and data management skills to multi-person teams tasked with solving low-to-moderately complex problems. The Engineer 2 - Embedded Product Analytics is expected to perform conventional, less complex analytical assignments where building a working knowledge of Caterpillar and the products, technologies, processes, services, and systems related to specific job assignments is expected.

**Job Duties**:
The Condition Monitoring, Analytics and Modeling group in Caterpillar is focused on developing, implementing and validating predictive models which predict the wear-out of various machine parts and systems. Typical activities include gathering (and cleaning) machine data, building mathematical control models using Matlab or Python, validating and testing the models against additional field data or developing the model into implementable, robust, embedded code. A few examples of the types of components our group has developed models to predict failure with include engine & hydraulic oil, hydraulic cylinder seals, transmission bearings/gears, and engine valves.

This position must manage their own development, continuously learning through experience and staying abreast of emerging technologies such as edge computing, operating system level virtualization, machine learning, Internet of Things, and online analytical processing. Key learning comes from gaining experience in product, process and systems definition, selecting the most appropriate tools and techniques for a project and collaborating with people who work outside of engineering as well as technical communication and documentation.

**Background/Experience**:
Requires bachelor degree in an accredited Engineering or Computer Science or Materials Science

1 to 3 years of relevant engineering experience.

Must have ability to communicate effectively in English with team members and others in the work group, as well as customers and suppliers. Highly desirable skills would include familiarity with Linux operating system, the ability to read and develop Python code, familiarity with machine and engine data protocols used by Caterpillar (J1939 and Ethernet), and the ability to read and develop Matlab/Simulink models

**The Caterpillar Code of Conduct states that we will select and place employees based on their qualifications for the job to be performed, without regard to race, religion, national origin, color, gender, gender identity, sexual orientation, age or disability. In this company we do not request pregnancy tests, nor HIV tests as requirements for employment entry, permanence or promotion.**

Caterpillar is an Equal Opportunity Employer (EEO).

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