DATA SCIENTIST II, CAT DIGITAL at Caterpillar
The Cat® Digital group is the digital and technology arm of Caterpillar Inc., responsible for bringing world class capabilities to our products and services. With almost one million connected assets worldwide, we're focused on using data, advanced analytics, and AI capabilities to help our customers build a better world. To accomplish this, we’re deploying analytics that generate insights, recommend optimized decisions, and improve products by intelligently integrating massive quantities of telematics information, transactional records, images, unstructured documents, and other data sources. Join our group of world-class data scientists and apply deep learning to remote sensor data to diagnose potential issues and schedule proactive repairs before failures arise. Or improve products and product recommendations by developing a detailed understanding of how customers use their Cat equipment. Or use the insights gained from equipment and customer profiles to design targeted commercial offerings that maximize customer value of Cat equipment fleets. The opportunity to make an impact is remarkable!
The Machine Condition Modeling & Analytics Team within Cat Digital’s Advanced IoT Analytics organization is looking for a talented and motivated Data Scientist to develop condition monitoring models to power asset management solutions for customers and dealers. You will use machine learning, deep learning, and statistics-based/physics-based analytics techniques on time-series sensor data, machine fault codes, inspections and analysis records, and other datasets to identify health anomalies, predict equipment failure modes, estimate remaining useful life, and build equipment risk models. Excellent python coding skills are paramount, but familiarity with modeling and analysis of heavy equipment engineering systems is a plus.
The Data Scientist will prototype, develop, iterate, test, and deploy models to production under the direction of a team lead, successfully meeting program objectives/timelines and solving problems with limited supervision. A fast learner with excellent communication skills, the successful candidate will collaborate effectively with diverse teams (including other data scientists, product design/simulation experts, platform/application developers, condition monitoring analysts) to develop analytics algorithms that enable condition monitoring commercial offerings of strategic importance.
Example projects include:
• Applying machine learning/deep learning to remote sensor data to diagnose potential issues and recommend proactive repairs before failure
• Developing major-component remaining useful life models that enable adaptive overhaul intervals while minimizing risk
• Enabling next-gen machine condition monitoring via digital twin capability development
• B.S. in data science, computer science, applied mathematics/statistics, physics, electrical, mechanical or industrial engineering
• 4-5 years of work experience (or M.S. plus 2-3 years)
• Strong python skills for data science (numpy, pandas, pyspark, pytorch, keras)
TOP CANDIDATE WILL ALSO HAVE:
• Demonstrated expertise applying machine learning / deep learning to telematics data
• Familiarity with modeling and analysis of heavy equipment systems (machine, engine, transmission, etc.)
• AWS Cloud Practitioner certification (or other advanced AWS certification)
ADDITIONAL DESIRED QUALIFICATIONS:
• Experience deploying production code on AWS in an Agile software development environment
• Excellent presentation, communication, interpersonal, and collaboration skills
• Demonstrated capability to take initiative and lead in the presence of ambiguity to deliver innovative solutions
Relocation is available for this position.
Visa sponsorship available for eligible applicants.
EEO/AA Employer. All qualified individuals - Including minorities, females, veterans and individuals with disabilities - are encouraged to apply.
Not ready to apply? Submit your information to our Talent Network here.