Data Scientist II- Data Algorithms & Optimization, Cat Digital

Caterpillar Inc.•Peoria, IL

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 Platform Analytics and AI team of Cat Digital and be responsible for delivering advanced analytics, data science, and machine learning solutions that support business decision-making, product innovation, and operational excellence. This position partners closely with analytics leaders, product teams, and technical stakeholders to translate complex business problems into scalable, data-driven solutions. The role plays a critical part in ensuring data quality, developing analytical models, and providing actionable insights that drive measurable business impact across digital initiatives.

Requirements

Business Statistics: Working knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.
Accuracy and Attention to Detail: Extensive understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.
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 programming to solve business challenges; ability to use tools, techniques and platforms in order to write and modify programming languages.
Requirements Analysis: Working knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.

Nice To Haves

Typically, a Bachelors, Masters, or PhD degree in Applied Statistics, Data Science, Business Analytics, Predictive Analytics, Business Intelligence & Analytics, Mathematics, Computer Science, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), or equivalent technical degree.
Hands-on experience: applying Python programming to solve business challenges.
advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc
practical applications of Machine Learning techniques such as Clustering, Logistic Regression, Random Forests, SVM or Neural Networks.
working with generative AI, with an understanding of strengths, limitations, and responsible use considerations.
Advanced experience in quantifying the costs, benefits, risks and chances for success before recommending a course of action.
In-depth technical and problem-solving skills and evidence of continuous learning in the analytics field
Working knowledge with cloud technologies (AWS, Azure, Google Cloud, etc.)
Advanced experience with version control / repositories such as GitHub
Experience operating in an Agile environment
Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively.

Responsibilities

Design, develop, and maintain advanced analytical models, including machine learning and statistical approaches, to support digital products and enterprise initiatives.
Analyze large, complex datasets to identify trends, patterns, and opportunities for improvement.
Partner with cross-functional teams to define analytical requirements and translate business questions into data science solutions.
Support data quality initiatives by validating data sources, identifying gaps, and recommending improvements.
Communicate insights and model results clearly to technical and non-technical stakeholders.
Contribute to continuous improvement of analytics tools, methodologies, and best practices within Cat Digital.