Lead Data Scientist - Artificial Intelligence R&D

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 solutions for our customers and dealers. With over 1.5 million connected assets worldwide, our teams use data, technology, advanced analytics, telematics and AI capabilities to help our customers build a better, more sustainable world.

Job Summary:   

The AI Research & Development (AI R&D) team at Cat Digital is seeking a Lead Data Scientist to serve as a senior technical leader at the intersection of applied AI, advanced technology, and forward‑looking research. This role focuses on designing, building, evaluating, and scaling AI prototypes and Proofs of Concept (POCs) with clear production intent, while also contributing to longer‑horizon research initiatives.

The Lead Data Scientist will work hands‑on across the full AI lifecycle, from data preparation and experimentation to model evaluation and production‑readiness, collaborating closely with Product, Engineering, and Business stakeholders to translate emerging AI capabilities into impactful enterprise solutions.

What You Will Do:

• Stay current with emerging AI research by conducting ongoing literature reviews across core AI workstreams such as speech/voice, vision, multimodal systems, retrieval, and autonomous agents, and actively apply relevant innovations to Cat Digital’s AI R&D portfolio.
• Assess and compare academic and industry advancements to guide architecture choices, experimentation strategy, and production‑readiness decisions.
• Synthesize research findings into practical, enterprise‑relevant insights that influence prototyping priorities and long‑term AI strategy.
• Lead hands‑on experimentation and development of advanced machine learning and generative AI solutions, including LLMs, multimodal models (text, vision, speech), retrieval‑augmented generation (RAG), agents, and simulation/digital‑twin use cases. 
• Design, build, and curate high‑quality datasets for training, fine‑tuning, validation, and evaluation of AI models at scale. 
• Define and execute rigorous model evaluation strategies, including benchmarking model quality, accuracy, latency, cost, robustness, and safety tradeoffs. 
• Drive rapid prototyping and POC development with a strong focus on reproducibility, experiment tracking, and observability to enable informed technical decision‑making. 
• Research, compare, and optimize model architectures, algorithms, and AI system designs to improve performance, scalability, and enterprise readiness. 
• Partner with Product and Engineering teams to translate research outcomes and prototypes into production‑ready capabilities, including defining technical requirements and success metrics. 
• Communicate complex technical findings and insights clearly to both technical and non‑technical stakeholders, influencing roadmap and investment decisions. 

What You Will Have:

• Structured AI Technology Research: Demonstrated experience conducting structured technology research and literature reviews in advanced AI domains, with the ability to translate theoretical innovation into applied, enterprise‑grade solutions.
• Applied Statistics & Quantitative Methods: Extensive experience applying statistical thinking to experimentation, evaluation, and decision‑making in ambiguous, research‑driven environments. 
• Analytical Rigor & Attention to Detail: Proven ability to design precise experiments, validate assumptions, and ensure accuracy and reproducibility of results. 
• Advanced Machine Learning & AI: Extensive knowledge o