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 Data Scientist. The Data Scientist will help shape how D.R. Horton applies advanced analytics, machine learning, and emerging AI capabilities to meaningful business problems. This role will explore data, build and validate models, translate findings into practical recommendations, and help move successful analytical ideas toward production use. The ideal candidate combines strong quantitative skills with curiosity, business judgment, and a desire to create measurable impact rather than models for their own sake. Success in this role means models and analyses that change real decisions, with clear evidence of business impact and a growing library of reusable work.

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

• Explore and prepare data, develop features, and build analytical and machine learning models for business use cases
• Evaluate models using appropriate technical and business metrics and clearly document assumptions and limitations
• Partner with business subject-matter experts (SMEs) to understand processes, decisions, constraints, and success measures
• Collaborate with data engineers and Forward Deployed Engineers (FDEs) to produce analytical logic and models
• Create clear visualizations, analyses, and presentations that translate technical results into business implications
• Contribute reusable code, features, evaluation approaches, and documentation that raise the standard for analytics and AI work across the team
• 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