Principal Data Scientist

Caterpillar Inc.•Peoria, IL

9d•Onsite

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. Job Summary: As part of Global Quality initiatives focused on customer back quality, process modernization, and value chain connectivity, this role accelerates the adoption of Artificial Intelligence across Global Quality and the Global Quality Data Domain. The AI Analyst serves as an individual contributor, leading Global Quality–sponsored AI initiatives while supporting enterprise AI projects that consume or leverage Global Quality data. This role partners closely with the AI Center of Excellence (AI COE) and plays a key role in improving data quality, accessibility, and analytics capabilities that support Modern Manufacturing initiatives. The ideal candidate brings a strong blend of quality domain knowledge, data science expertise, and software or analytics experience, with the ability to translate complex data into meaningful business insights.

Requirements

Candidates should possess a Bachelor’s degree or higher, or demonstrate equivalent knowledge through extensive professional expertise.
Business Statistics Apply advanced statistical methods to analyze trends, variation, probability, and correlations across complex datasets. Design and execute statistical evaluations that inform data‑driven business decisions. Serve as a subject‑matter expert in statistical analysis, guiding best practices across the organization. Establish guidelines for selecting and applying appropriate statistical techniques.
Machine Learning Lead development and application of machine learning algorithms to solve complex business and quality challenges. Identify opportunities where machine learning solutions can improve processes, insights, or outcomes. Guide organizational strategy related to AI and machine learning adoption. Stay current on emerging machine learning trends and technologies and assess their applicability to the business.
Query and Database Access Tools Demonstrate deep expertise in query and database access tools across multiple platforms. Lead evaluation and adoption of new data access technologies and techniques. Provide technical guidance on efficient data extraction, transformation, and usage. Help establish and update technical standards related to data access and querying.

Responsibilities

Lead Global Quality AI initiatives, serving as an individual contributor and technical expert.
Act as a primary point of contact between Global Quality and the AI Center of Excellence (AI COE).
Direct large‑scale data gathering, data mining, and data processing efforts, including development of robust data models.
Support data staging, data views, and data definitions across enterprise platforms including Snowflake, Alation, and LeanIX.
Drive data quality improvements within native applications and enterprise data environments.
Enable Modern Manufacturing initiatives through improved data access, structure, and analytics capabilities.
Define requirements and scope for advanced data analyses and AI solutions.
Apply machine learning, natural language processing, and text analytics to unlock insights from structured and unstructured data.
Conduct research on data model optimization and algorithms to improve accuracy, scalability, and effectiveness.
Present insights, findings, and recommendations to stakeholders using data visualization tools such as Power BI.