Data Scientist II, Downtime and Condition Monitoring

Caterpillar•Chicago, IL

8d•Hybrid

About The Position

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. Cat Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital solutions for our customers and dealers. With over 1.5 million connected assets worldwide, our teams use data, technology, advanced analytics, telematics, and AI capabilities to help our customers build a better, more sustainable world. Job Summary: Join the Condition Monitoring Analytics team of Cat Digital and perform analytical and statistical modelling and initiatives on huge amount of data to support our Service Growth and downtime prevention strategy.

Requirements

Analytical Thinking: Working knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Machine Learning: Working knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
Programming Languages: Working knowledge of basic concepts and capabilities of applying Python and SQL programming to solve business challenges; ability to use tools, techniques and platforms in order to write and modify programming languages.
Query and Database Access Tools: Working knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.

Nice To Haves

Typically, a Bachelors, Masters, or PhD degree in Applied Statistics, Physics, Data Science, Business Analytics, Predictive Analytics, Business Intelligence & Analytics, Mathematics, Computer Science, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), or equivalent technical degree .
Extensive experience applying Python (NumPy, SciPy, pandas, etc.) and SQL programming to solve business challenges is a must
Extensive experience with advanced data analysis and statistical methods (typically 4+ years)
Extensive experience in practical applications of Machine Learning techniques such as Clustering, Logistic Regression, Random Forests, SVM or Neural Networks.
Working experience with heavy equipment engineering is an advantage.
In-depth technical and problem-solving skills and evidence of continuous learning in the analytics field
Advanced experience with version control / repositories such as GitHub
Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.

Responsibilities

Performing the data gathering, mining and processing processes in huge volume; creating appropriate data models.
Exploring, promoting, and implementing advanced statistical techniques (such as time series, NLP, genAI…), including tests, validation and delivery
Implement innovative data model optimization framework and algorithms to improve effectiveness and accuracy on models in production.
Provide support to technical partners as well as business partners to drive adoption
Defining requirements and scope of data analyses; create documentation, compelling presentations and visualizations to explain complex technical algorithms and impacts into understandable business language