Senior Data Scientist

Career Area:

Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc.

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.

For Caterpillar, Connectivity means using technology to extract data from our machines and engines and transform it into valuable recommendations and insights to help customers make better, more informed decisions and help Caterpillar make robust products with the lowest total ownership cost. Our products generate and process large amounts of data from sensors, on-board models, and control algorithms in real-time, creating real-world machine usage information to provide condition monitoring and fleet management services.

The Senior Data Scientist will analyze large and complex datasets from Caterpillar’s connected field assets to identify trends, opportunities, and insights that create business and customer value. This role will focus on turning machine and connectivity data into meaningful, actionable recommendations that support better decision-making across the organization.

In this position, you will work closely with dealer- and customer-facing teams to understand business needs, develop data-driven solutions, and translate analytical findings into practical actions. You will support applications across Construction Industries, Resource Industries, and Power & Energy while helping expand how Caterpillar uses connected asset data to improve products, services, and the customer experience.

What You Will Do:

• Analyze data from Caterpillar’s connected field assets to identify machine usage trends, performance issues, and opportunities to improve customer outcomes.
• Develop insights that help dealer- and customer-facing teams proactively identify equipment issues and make more informed recommendations.
• Turn connectivity and machine data into actionable business insights, rather than simply reporting or passing along data.
• Partner across Construction Industries, Resource Industries, and Power & Energy to address real-world equipment and fleet challenges using connected asset data.
• Develop analytical models and data-driven solutions that support condition monitoring, fleet management, and improved product and service decisions.
  

What You Will Have:

• Business Statistics: 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.
• Analytical Thinking: 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: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
• Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.
• Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.
  

Considerations For Top Candidates:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related technical field.
• 5–8+ years of experience in data science, advanced analytics, data engineering, or a related field.
• Experience working with large, complex datasets and translating data into actionable business or customer insights.
• Strong experience in Python, SQL, statistical analysis, machine learning, and data modeling.
• Experience developing and deploying AI/ML models, including exposure to Agentic AI, AI agents, or autonomous AI workflows.
• Experience using equipment, IoT, telematics, sensor, or other connected asset data to solve real-world business problems.
• Demonstrated ability to take analytical findings beyond reporting and turn insights into recommendations that business, dealer, or customer-facing teams can act on.
  

Additional Information:

• This position requires the candidate to work full-time at the Irving, TX office.
• Domestic relocation assistance is NOT available for this position.
• Visa sponsorship is NOT available with this position.
• This position will require up to 10% travel.
• #LI

Summary Pay Range:

$112,710.00 - $183,140.00

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

This position requires working onsite five days a week.Visa Sponsorship is not available for this position.

Posting Dates:

Any offer of employment is conditioned upon the successful completion of a drug screen.

Caterpillar is an Equal Opportunity Employer, Including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.

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