Lead 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.

The Cat® Digital group is the digital and technology arm of Caterpillar Inc., responsible for bringing world class capabilities to our products and services. With over 1.5 million connected assets worldwide, we're focused on using data, advanced analytics, and AI capabilities to help our customers build a better world.    Job Summary:  eCommerce is a key digital enabler to Caterpillar’s aftermarket parts and services growth strategy. Delivering on the Caterpillar brand promise of premium, high-quality solutions is an important element in accelerating the development and deployment of Caterpillar’s expanded capabilities in eCommerce. The Lead data scientist – Search is responsible for building the core search AI/ML/LLM models and overseeing the execution of advanced search algorithms. This role combines strategic vision, hands-on AI/ML expertise, and leadership to build scalable, high-performance search algorithms that deliver exceptional user experiences. If you want to enhance customer search experiences and lead scalable platforms, this role lets you make a significant impact.

Technical Strategy: Define and implement a long-term technical vision for the search platform to ensure scalability and adaptability to growing data volumes and query complexity.

Leadership: Mentor and guide a team of search engineers through technical reviews, best practices, and collaborative problem-solving. Feature Development: Introduce advanced capabilities such as NLP, vector search, and personalization to enhance relevance and accuracy. Data Analysis & Optimization: Build search capabilities with measurable KPIs (e.g., CTR, Query Distribution, Zero Search) and leverage analytics to continuously improve search performance. Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to align search initiatives with business objectives Algorithm Development & Modeling Optimization: Profile and tune deep learning algorithms for maximum search efficiency for keyword matching, user data and behavior, preferences, popularity, and more. Behavioral Models :  Profile the end-users’ behaviors and signals and fine-tune models to reflect to rearrange the search facet values Context Models: Leverage AI/MI/LLM models to Discern User Intent and capture in relevant search categories Categorization Models to build fitment recommendation with engineering information Personalization models: Rule based segmentation, ML based recommendation models, PFM – SSL models and Implicit Personalization models to enhance the search What You Will Have: Search AI/ML Models : Strong track record to deploy Search related ML models in large industrial /automobile / Manufacturing parts application (Learning-Rank, Lambda MART, Deep Ranking Models ) Generative AI & LLMs: Proficiency in Fine-tuning and Prompt Engineering for Large Language Models, specifically using Retrieval-Augmented Generation (RAG), Indexing models BM25, Sematic Retrieval, Query rewrite etc ML Platform Experience: Proven ability to work with large-scale search logs, Product data and build robust future/label pipelines and deploy models thru MLOps/ML platforms and API’s in Cloud environment (AWS/Azure/GCP) Business Statistics: Extensive experience with statistical tools, processes, and practices to describe business results in measurable scales; ability to use