Data Scientist I - AI & Risk Modeling

Key Skills

Aartificial intelligence, Analytical and Problem solving, AWS, Azure, Data science techniques, Deep Learning, Google Cloud Platform (GCP), Keras software library, Machine learning techniques, Pandas, PySpark, PyTorch, Risk modeling, Software Development

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.

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 over 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 customized service offerings that maximize our customers’ value of their Cat equipment fleets. You’ll have significant opportunity to do meaningful work that makes a real impact.

JOB DUTIES: 

The Aftermarket Analytics Team within Cat Digital 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 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 required. Familiarity with condition monitoring, or related modeling and analysis of heavy equipment engineering systems, is a plus.

The key role of this Data Scientist position is to move from learning and assisting others to learning to contribute independently. The Data Scientist is expected to be familiar with the company’s processes, products, and organization. Work is typically directed by a project or team lead who might review both methods and results. Decisions on routine, limited risk issues that may affect the project team, suppliers or internal customers may be made by this position. Challenges include meeting expectations in delivering results, learning to consider alternative courses of actions, and making timely decisions. Individuals in this position might expect to have several assignments allowing them to gain experience on multiple projects. They will be expected to apply theory and concept in contributing to the solution in the assigned area.

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 appropriate 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 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

BASIC QUALIFICATIONS: 

• M.S. in data science, computer science, applied mathematics/statistics, engineering, physics, or similar field with quantitative coursework
• 1-2 years work experience in data science and/or software development 
• Strong python skills for data science (numpy, pandas, pyspark, pytorch, keras, etc.)

TOP CANDIDATE WILL ALSO HAVE: 

• Demonstrated practical application of advanced statistical methods, machine learning, and deep learning to solve technical or business challenges
• Familiarity with condition monitoring or modeling/analysis of heavy equipment systems (automotive, aerospace, engine, transmission, construction, mining, industrial, etc.)
• Experience deploying production code in cloud environments (AWS, Azure, GCP)
• Strong technical and problem-solving skills, with evidence of continuous learning in data science
• Initiative to research and apply new methods and digital technologies to exceed customer expectations

ADDITIONAL DETAILS: 

This position has the option to be based out of either our Chicago, IL; Peoria, IL or Champaign, IL offices with a flexible hybrid work environment.