Principal Data Scientist - Search

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.

Your Work Shapes the World at Caterpillar Inc.

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:

 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 principal data scientist – Search Quality Framework is responsible for architecting and implementing an advanced, AI-driven search quality framework that rigorously validates whether search enhancements deliver the intended outcomes. This role leverages sophisticated data science skills, including designing and deploying machine learning (ML) and deep learning models tailored for search relevance, ranking, and personalization. Key responsibilities involve developing automated evaluation pipelines using statistical analysis, A/B testing, and custom metrics to measure the impact of new algorithms on user experience and business goals This role combines strategic vision, hands-on AI/ML expertise, and leadership to build scalable, high-performance search algorithms that deliver exceptional user experiences.

What You Will Do:

• 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.

• Team 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 Models: 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 : Leverage the Graph based models to build fitment recommendation based on Bill of materials.

• 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)

• Search & Data Quality Frameworks: Extensive background in building frameworks that continuously monitor and improve search accuracy.

• 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: Ex