Data Scientist I, Lens Customer Analytics

Caterpillar Inc.•Peoria, IL

5d•$89,210 - $144,960•Onsite

About The Position

Join Caterpillar's Customer Analytics and Applied AI team within Cat Digital to perform analytical tasks and initiatives using large volumes of data in support of data-driven business decisions and development. The Lens capability uses historical customer and dealer data to identify real-world customer behavior and unmet needs, enabling proactive customer support. The role gathers, mines, and processes large volumes of data and creates appropriate data models. It explores and implements semantic data capabilities using natural language processing, text analysis, and machine learning. The position defines analysis requirements and scope, communicates potential business insights to management using data visualization technologies, and researches data model optimization and algorithms to improve the effectiveness and accuracy of analyses. The position is based at Caterpillar's Peoria, Illinois office. Relocation assistance and visa sponsorship are not available.

Requirements

Working knowledge of business statistics and the ability to use statistical tools and processes to support business decisions.
Working understanding of accuracy and attention to detail, with the ability to complete tasks precisely.
Working knowledge of analytical techniques and tools, including determining root causes and developing alternative solutions.
Basic knowledge of machine learning principles, technologies, and algorithms, and the ability to develop, implement, and deliver related systems, products, and services.
Working knowledge of developing with AI agents and GitHub Copilot.
Basic knowledge of Python programming concepts and capabilities and the ability to apply programming tools and techniques to business challenges.
Working knowledge of data management systems and tools for searching, extracting, and formatting data.
Working knowledge of requirements analysis methods and the ability to elicit, analyze, and record functional and non-functional business requirements.
Typically, a master's or PhD in a relevant technical field or equivalent, with 2+ years of experience.
Extensive experience applying Python, including NumPy, SciPy, and pandas, to business challenges.
Typically 1+ years of extensive experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, and statistical process control.
Extensive experience with practical machine learning techniques such as clustering, logistic regression, random forests, SVM, or neural networks.
Extensive experience with AI tools and agentic development, such as LangChain, Bedrock, and GitHub Copilot.
Advanced experience quantifying costs, benefits, risks, and likelihood of success when recommending a course of action.
Must demonstrate strong initiative, interpersonal skills, and effective communication.

Nice To Haves

Working experience with customer analytics.
Experience designing or developing analytics for heavy equipment industries, such as automotive, aerospace, engines, transmission, construction, mining, or industrial.
In-depth technical and problem-solving skills and evidence of continuous learning in analytics.
Working knowledge of cloud technologies such as AWS, Azure, or Google Cloud.
Advanced experience with version control and repositories such as GitHub.
Experience operating in an Agile environment.

Responsibilities

Gather, mine, and process large volumes of data and create appropriate data models.
Explore, promote, and implement semantic data capabilities using natural language processing, text analysis, and machine learning techniques.
Define requirements and scope for data analyses; present and report potential business insights to management using data visualization technologies.
Research data model optimization and algorithms to improve the effectiveness and accuracy of data analyses.