Lead Data Scientist, Cat Digital
Listed on 2026-08-31
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IT/Tech
Data Analyst, Data Scientist, AI Engineer (Applied/Software)
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.
Cat® Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital and analytics solutions for our customers and dealers.
Working with a Fortune 100 leader, you can build your career on a global scale and take advantage of development opportunities with emerging technologies.
We’ve created an inclusive environment for you to explore your passions, make an impact and do the work that really matters.
Job Summary:As a Lead Aftermarket Data Scientist in the global aftermarket analytics team of Cat Digital, you will be tasked with enabling services growth by collaborating with other teams such as aftermarket leads and insights, business segments, and Cat Digital Analytics to maximize the value extraction of our digital products and services.
With over 1.5M connected assets worldwide, using the latest technology, data is generated continuously by Cat® equipment in our business and in the industries we serve.
Your responsibility will be using advanced analytics and AI capabilities on this vast amount of data to help our customers build a better world.
To accomplish these daunting challenges, this role will require a skillset in advanced statistical techniques (machine learning, AI, etc.) as well as existing or ability to quickly gain domain knowledge of heavy equipment, industries we serve, and the business practices therein.
What You Will Do:Participate on 3-4 projects concurrently exploring, implementing, and promoting advanced statistical methods and/or digital methods to solve medium to complex business problems. Holds team accountable for driving and achieving results and owns all aspects of assigned projects Proactively prioritizes and drives opportunities with very minimal managerial support Work with and use Caterpillar’s Aftermarket data to understand and develop analytical solutions for medium to complex business problems.
Develops exceptionally compelling messaging, written documents, and presentation materials, and is a compelling speaker in a wide variety of situations Leads interactions with cross-functional teams to engage diverse participants and ensure effective consensus and collaboration Demonstrate good knowledge of Caterpillar Inc.; its products and services; its internal systems, processes, and procedures; and its relevant external influences (competitors, laws and regulations, market conditions, etc.)
to meet or exceed customer expectations.
Extensive 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.
Expert ability to use logic and intuition to make inferences about the meaning of the data or unexpected results in data, and arrives at actionable conclusions and implements the corresponding actions.
Leadership & Collaboration in Analytics:Expert level experience in autonomously working closely with cross-functional teams, providing data-driven insights, collaborating on projects, developing good communication, and effectively presenting material to solve medium to complex business challenges.
Business Statistics:Extensive experience with 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.
Machine Learning:Extensive knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
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