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Lead development and improvement of vehicle pricing models by applying machine learning and statistical techniques, feature engineering, and controlled experiments; present insights to senior leaders; research modeling innovations and influence the team's modeling roadmap; communicate model behavior to stakeholders.

The Data Engineer II will design, build, and maintain data pipelines, ensuring data governance and security. Responsibilities include coding in Python, managing data processing, and collaborating with data teams.

As a Data Science Manager, you'll drive personalization initiatives through data science, manage experimentation, and lead technical innovation in ML algorithms at CarMax.

Lead implementation and configuration of Oracle Cloud Financials, gather and translate business requirements into technical user stories, drive data conversion/mapping, collaborate with SI and cross-functional teams, build/test/train/support solutions, and produce functional specs and SOPs to simplify finance processes.

Lead teams that design, build, and operate application systems for customer acquisition and discovery. Partner with stakeholders on SEO/GEO, content, personalization, and AI-powered discovery. Drive AI/ML/NLP adoption, ensure system health, accessibility, experimentation, and measurement, and grow engineering talent while guiding architecture, integrations, and secure scalable operations.

The Analyst II, Information Risk Management focuses on managing privacy operations, coordinating data requests, executing privacy assessments, and improving privacy processes using automation and AI.

The Sr. Software Engineer will develop and maintain REST APIs and data integrations on Azure, ensuring effective master data management and performance improvements.

Lead development and deployment of predictive customer progression models across the full lifecycle. Analyze large, complex datasets, design experiments (A/B tests), collaborate with Product/Engineering/Operations, and mentor a team of data scientists while driving scalable modeling infrastructure and communicating insights to influence business strategy.

Lead development of optimal logistics planning strategies and AI-driven models to autonomously plan vehicle moves. Build and manage a 4-7 person data science team, implement production-ready optimization and ML systems, collaborate cross-functionally to deploy solutions, and measure impact to deliver $10-25M/yr in incremental value.

Lead design and implementation of developer platform and AI-assisted tooling (MCP, skills, agents), build integrations, govern patterns, champion engineering best practices, instrument tooling, mentor engineers, and drive adoption across the organization.