Career Area:

Job Description:

The SPPD Supplier Quality team is seeking a Data Scientist who can transform complex enterprise data into actionable insights that drive quality improvement, reduce warranty exposure, and enhance supplier performance across the organization.

In this role, you will leverage machine learning, predictive analytics, business intelligence, and data visualization to identify emerging risks, uncover performance trends, and support critical business decisions. Working at the intersection of data science, analytics, and business strategy, you'll develop predictive models, build scalable analytics solutions, and create AI-enabled tools that help stakeholders make faster, smarter decisions.

This position also supports the organization's growing investment in artificial intelligence, automation, and Copilot-enabled solutions, offering an opportunity to help shape future analytics capabilities while working with emerging technologies.

What makes this role exciting:

This is a highly visible role supporting some of the organization's most strategic initiatives. Your work will directly influence supplier quality performance and support warranty recovery efforts. You'll partner with senior leaders across the enterprise, including procurement and executive-level stakeholders, to solve complex business challenges through analytics and machine learning.

Unlike many analytics roles where insights remain theoretical, you'll see your models, dashboards, and recommendations translate into measurable operational and financial outcomes. You'll have the opportunity to influence high-profile projects while helping define how AI, automation, and citizen-developer solutions are leveraged across Supplier Quality.

What you will do:

• Develop and maintain business intelligence tools, dashboards, and data visualizations that provide actionable insights into supplier quality and warranty performance.

• Design, build, and enhance predictive analytics and machine learning models that identify quality risks, supplier trends, and opportunities for business improvement.

• Analyze large, complex datasets from multiple enterprise systems to uncover patterns, detect anomalies, and generate data-driven recommendations.

• Collaborate with quality, procurement, engineering, and business stakeholders to translate operational challenges into analytical solutions.

• Research, design, and document data specifications throughout the production lifecycle.

• Evaluate and improve data quality, ensuring the integrity and reliability of analytics outputs and machine learning models.

• Utilize SQL and other data programming languages to support analytics, reporting, model development, and system enhancements.

• Prepare, transform, and integrate structured and unstructured data to support predictive modeling, machine learning, AI, and advanced analytics initiatives.

• Contribute to cloud-based analytics and AI environments, supporting scalable data platforms and model deployment.

• Support emerging citizen-developer, automation, and Copilot-enabled capabilities that improve business efficiency and decision-making.

• Communicate analytical findings and technical concepts in a clear, compelling manner to stakeholders across all organizational levels.

What skills you have:

ETL Process

Knowledge of the extraction, transformation, and loading (ETL) process; ability to develop a database through the ETL process.

• Experience preparing, transforming, and integrating large datasets for advanced analytics, machine learning, and AI applications.

• Ability to ensure data accuracy, consistency, and usability across analytics environments.

• Experience supporting data pipelines that power dashboards, predictive models, and business intelligence tools.

Value Realization

Knowledge of value realization methods; ability to plan, execute, monitor, and manage business activities and resources to determine and achieve the actual value from a business initiative as estimated in an associated business case.

• Demonstrated ability to connect analytics solutions to measurable business outcomes.

• Ability to identify opportunities where machine learning, predictive analytics, and AI can create value through quality improvement, warranty reduction, risk mitigation, or supplier performance gains.

• Experience supporting data-driven decision-making through quantifiable business impact.

Communicating Complex Concepts

Knowledge of effective presentation tools and techniques to ensure clear understanding; ability to use summarization and simplification techniques to explain complex technical concepts in simple, clear language appropriate to the audience.

• Ability to communicate machine learning models, statistical findings, and technical recommendations to both technical and non-technical audiences.

• Experience developing dashboards, visualizations, and presentations that drive action and business understanding.

• Strong consultative communication skills and ability to influence decisions through data storytelling.

Modeling: Data, Process, Events, Objects

Knowledge of data, process, and events; ability to use tools and techniques for analyzing and documenting logical relationships among data, processes, or events.

• Experience applying data modeling techniques to support predictive analytics and machine learning initiatives.

• Ability to analyze relationships across enterprise datasets and develop scalable analytical frameworks.

• Experience documenting data flows, structures, and analytical models.

Information Management

Knowledge of an organization's existing and planned Information Architecture and Information Management methodology; ability to collect and manage information from different sources and distribute information to enhance operational efficiency.

• Ability to manage large volumes of structured and unstructured data from multiple enterprise sources.

• Experience supporting analytics, AI, and machine learning initiatives through effective information management practices.

• Understanding of how data governance and information architecture enable scalable analytics solutions.

Cloud Computing

Knowledge of cloud-based solutions and ability to design, implement, and manage them.

• Experience supporting machine learning, analytics, and data workloads within cloud environments.

• Ability to contribute to scalable cloud-based data and AI solutions.

• Familiarity with cloud-based data storage, processing, and analytical platforms.

Database Design

Knowledge of database systems; ability to establish a data model for designing an organization's database that runs effectively and efficiently for better business outcomes.

• Experience developing data structures that support reporting, analytics, predictive modeling, and machine learning datasets.

• Ability to optimize data models to support scalable analytics and business intelligence solutions.

Top Candidates Will Also Have:

• A strong background in manufacturing, supplier quality, warranty analytics, procurement analytics, or related operational environments.

• Demonstrated success developing predictive analytics and machine learning models that drive measurable business outcomes.

• Hands-on experience with Python, R, or similar tools used for advanced analytics, data science, and model development.

• Expertise building business intelligence dashboards and visualizations that clearly communicate insights and model outputs.

• Familiarity with artificial intelligence technologies, including GitHub Copilot, Copilot Studio, or related AI-enabled platforms.

• Working knowledge of data architecture, enterprise data platforms, and information management practices.

• Experience applying statistical analysis, feature engineering, model evaluation, and machine learning methodologies to solve business problems.

• Success quantifying business value from analytics initiatives, including cost savings, process improvements, risk reduction, or warranty recovery.

• A proven ability to balance deep technical capability with strong stakeholder engagement and business communication.

• Experience partnering across quality, procurement, engineering, and leadership teams to deliver data-driven solutions.

Additional information:

• Primary Work Location: This role is based in Peoria, IL and requires on-site presence five days per week.

• Travel: This position may require up to 5% travel.

• Relocation: Relocation assistance is not available.

• Sponsorship: Visa sponsorship, international assignments, and payroll transfers are not available for this role.

Summary Pay Range:

Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar. 

Benefits:

Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.

• Medical, dental, and vision benefits*

• Paid time off plan (Vacation, Holidays, Volunteer, etc.)*

• 401(k) savings plans*

• Health Savings Account (HSA)*

• Flexible Spending Accounts (FSAs)*

• Health Lifestyle Programs*

• Employee Assistance Program*

• Voluntary Benefits and Employee Discounts*

• Career Development*

• Incentive bonus*

• Disability benefits

• Life Insurance

• Parental leave

• Adoption benefits

• Tuition Reimbursement

* These benefits also apply to part-time employees

Posting Dates: