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.

Job Description

The Cat® Digital group is the digital and technology arm of Caterpillar Inc., responsible for delivering world-class digital capabilities across our products and services. With more than 1.5 million connected assets globally, Cat Digital leverages data, advanced analytics, and AI to help customers build a better, more sustainable world.

Job Summary

eCommerce is a key digital enabler in Caterpillar’s aftermarket parts and services growth strategy. The Senior Data Scientist – Search plays a critical hands-on role in designing, building, and deploying advanced AI/ML and search relevance models that power scalable, high-quality enterprise search experiences.

This role focuses on end-to-end model development, experimentation, and optimization for search and discovery, working closely with product, engineering, and platform teams to improve relevance, personalization, and business outcomes.

What You Will Do

Search Model Development & Optimization

Design, develop, and deploy ML, deep learning, and relevance models for enterprise search, including ranking, retrieval, and semantic search

Implement and fine-tune Learning-to-Rank models (e.g., LambdaMART, deep ranking models) to improve result relevance and user satisfaction

Optimize search pipelines using keyword, behavioral, contextual, and semantic signals

AI, NLP, and Generative Search

Build and enhance NLP-driven capabilities such as query understanding, intent detection, and query rewriting

Apply Generative AI and LLM techniques including fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG) for search use cases

Work with retrieval methods such as BM25, semantic retrieval, and vector search

Behavioral, Contextual, and Personalization Models

Develop behavioural models leveraging user signals, clickstream data, and search interactions

Build contextual intent models to improve categorization and relevance

Implement personalization models, including rule-based segmentation, ML-based recommendations, and implicit personalization

Data Analysis & Experimentation

Analyze large-scale search logs and product data to identify relevance gaps and improvement opportunities

Define and track search KPIs (CTR, zero-result searches, query distribution, relevance metrics)

Design and execute A/B tests to validate model and feature improvements (nice to have)

MLOps & Platform Collaboration

Build robust feature engineering, labeling, and model pipelines

Deploy and monitor models using MLOps frameworks and cloud-native platforms (AWS, Azure, or GCP)

Collaborate with engineering teams to operationalize models through APIs and scalable services

Cross-Functional Collaboration

Partner with product managers, engineers, and data science peers to align search capabilities with business objectives

Contribute technical insights, documentation, and recommendations to influence product and platform decisions

What You Will Have

Core Technical Skills

Strong experience developing and deploying ML models for search, recommendation, or relevance-driven systems

Hands-on expertise with Python and data science libraries (NumPy, pandas, SciPy, etc.)

Solid understanding of machine learning techniques including ranking, clustering, regression, and neural networks

Experience working with large-scale datasets, search logs, and production ML systems

AI / ML & Search Experience

Practical experience with search relevance techniques such as Learning-to-Rank, semantic retrieval, and NLP

Exposure to Generative AI and LLM-based search solutions (RAG, prompt engineering, embeddings)

Familiarity with personalization and recommendation systems

Platform & Cloud

Experience deploying models through ML platforms, APIs, and cloud environments (AWS, Azure, or GCP)

Working knowledge of version control systems (Git/GitHub)

Experience operating in Agile delivery environments

Analytical & Business Acumen

Strong statistical knowledge to translate business problems into measurable analytics solutions

Ability to analyze results, identify root causes, and recommend data-driven improvements

Effective communication skills to explain complex models and insights to technical and non-technical stakeholders

Considerations for Top Candidates

Bachelor’s or Master’s degree (or PhD) in Data Science, Statistics, Computer Science, Engineering, Mathematics, or equivalent technical field

Typically 5+ years of experience in applied data science, machine learning, or search-related systems

Experience with industrial, manufacturing, automotive, or large-scale enterprise datasets is a strong plus

Familiarity with heavy equipment engineering data or eCommerce search domains is beneficial

This position requires working onsite five days a week.

Relocation is available for this position.

Posting Dates:

November 2, 2026 - November 2, 2026

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

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