Senior Data Scientist

D.R. Horton, Inc., the largest homebuilder in the U.S., was founded in 1978 and is a publicly traded company on the New York Stock Exchange. It is engaged in the construction and sale of high-quality homes designed principally for the entry-level and first time move-up markets. The Company also provides mortgage financing and title services for homebuyers through its mortgage and title subsidiaries. Please visit our website at www.drhorton.com for more information.

As the nation's largest homebuilder by volume, D.R. Horton is transforming how it uses data, AI, and digital solutions for the next generation of homebuilding, and we pair the reach of a national enterprise with a culture built on local ownership, practical innovation, and deep business partnerships. Our teams focus on solutions that work in the field and deliver real results, not technology for its own sake. In this role, you'll have a critical opportunity to shape modern capabilities that will influence how the company operates for years to come.

D.R. Horton, Inc. is currently looking for a Senior Data Scientist. The Senior Data Scientist will help turn complex data into advanced analytics, machine learning, and AI solutions that improve decisions and business performance. This role will independently lead modeling work from problem framing through validation and deployment, partner closely with business and engineering teams, and help establish repeatable practices for production analytics and AI. The ideal candidate combines technical depth, curiosity, and practical business judgment with a focus on measurable outcomes. Success in this role means models delivered end to end that improve a measurable business outcome and are monitored in production.

Essential Duties and Responsibilities include the following. Other duties may be assigned.

• Develop, validate, and document predictive, forecasting, optimization, statistical, and machine learning models for assigned priority use cases
• Perform exploratory analysis and feature engineering using enterprise data while identifying data quality and measurement limitations
• Define evaluation approaches that reflect the actual business decision, operational constraints, and cost of errors
• Partner with Forward Deployed Engineers (FDEs) and engineers to integrate models into workflows, applications, APIs, and production monitoring
• Communicate findings, uncertainty, assumptions, and recommendations clearly to business partners
• Represent the function in cross-functional discovery, architecture, governance, operational-readiness, and continuous-improvement activities as appropriate
• Stay current on relevant data, AI, digital, software, and industry practices and apply new capabilities when they create practical business value
• Identify, shape, and pilot new opportunities where data, AI, and digital capabilities can create business value, operating with an owner's mindset and a bias toward building, testing, and learning quickly
• Conduct all business in a professional and ethical manner
• Ability to travel overnight