Data Scientist

Caterpillar is seeking a Data Scientist to support its Power and Energy Drivetrain team through analysis of large volumes of data and development of practical, data-driven solutions. This onsite role focuses on building and refining data models, applying Natural Language Processing and machine learning, and communicating findings to management through data visualization.

What you’ll do

• Lead data gathering, data mining, and data processing for very large volumes, creating data models that fit the analysis goals.
• Explore, promote, and implement semantic data capabilities using Natural Language Processing, text analysis, and machine learning techniques.
• Help define analysis requirements and scope, then present business insights to management using data visualization technologies.
• Conduct research to optimize data models and algorithms to improve effectiveness and accuracy.
• Design and develop solutions by collaborating with senior stakeholders and business users, gathering VOB/VOC and business requirements, and preparing implementation plans for deployment.
• Contribute to strategic initiatives, including development of standardized best practices, offerings, services, and associated tools and training.

What you bring

• Knowledge of statistical tools, processes, and practices to describe business results in measurable terms and support business decisions.
• Ability to explain the basic decision process tied to specific statistics.
• Capability to work with basic statistical functions on a spreadsheet or calculator.
• Understanding of common statistical errors, misinterpretations, and misrepresentations, including why they occur.
• Familiarity with sample size characteristics, normal distributions, and standard deviation; ability to generate and interpret basic statistical data.
• Commitment to accuracy, with the ability to complete tasks with high precision.
• Strong attention to detail when processing large quantities of information and an ability to balance speed and accuracy.
• Experience evaluating and contributing to best practices, including cross-checking approaches and quality assurance tools, techniques, and standards.
• Ability to use techniques that support effective analysis, identify root causes of organizational problems, and propose alternative solutions.
• Comfort defining problems and assessing significance, and comparing two or more alternative solutions systematically.
• Skill using visual/analytical methods such as flow charts, Pareto charts, and fish diagrams to identify meaningful data patterns.
• Ability to apply logic and intuition to interpret data meaning and draw conclusions.
• Knowledge of machine learning principles, technologies, and algorithms, with ability to develop, implement, and deliver related systems, products, and services.
• Experience completing tasks and initiatives using machine learning technologies, including search engine optimization.
• Use of tools and techniques for descriptive and inferential statistics.
• Hands-on use of programming languages and tools for machine learning, including R and Python.
• Ability to perform data mining and cleaning activities.
• Capacity to diagnose and report minor or routine issues related to programming languages.
• Knowledge of data management systems, including using and supporting access for searching, extracting, and formatting data.
• Ability to define, create, and test simple queries using command language in a specific environment.
• Ability to apply query tools to connect to a data warehouse, analyze query access path information and results, and use tested query statements to retrieve, insert, update, and delete information.
• Working knowledge of advanced query features such as sorting, filtering, and making simple calculations.
• Knowledge of business process improvement best practices, including methods to identify, evaluate, introduce, and implement more efficient approaches.
• Ability to move beyond reporting by translating data into recommendations that drive business decisions and process improvements.
• Experience working with enterprise data platforms such as Snowflake, including querying, validating, and connecting data sources to reporting and visualization tools.

Technologies you’ll use

• Natural Language Processing
• Machine learning
• Search engine optimization
• R
• Python
• Snowflake

Location and schedule

• East Peoria, IL (onsite)
• Onsite requirement: five days a week

Compensation

Pay range: USD 97,530 - 158,480 per year.

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

Additional information

• Relocation is not available for this position.
• Sponsorship is not offered for this position.
• Visa Sponsorship is not available for this position.

Posting dates: September 17, 2026 - September 24, 2026