Senior Data Scientist, Search and Recommendations

CarMax•Richmond, VA

1d•Onsite

About The Position

As a Sr. Data Scientist at CarMax, you’ll play a pivotal role in shaping the future of automotive retail through advanced analytics and innovative modeling. CarMax disrupted the industry over 20 years ago and remains the market leader in a $500B+ sector. Our success is built on best-in-class financial performance, customer satisfaction, and associate engagement. To maintain our analytics-driven competitive edge, we leverage algorithm-based pricing and inventory systems. We’re seeking passionate, strategic thinkers who thrive on solving complex problems and driving business-critical decisions through data.

Requirements

Strong expertise in predictive modeling and statistical analysis, with a passion for continuous learning.
Proven ability to solve complex problems using analytics and influence outcomes.
Experience managing projects and delivering results on time.
Excellent communication skills to explain technical concepts clearly.
Track record of building collaborative relationships and driving team success.
Undergraduate degree in a quantitative discipline.
2+ years of experience in strategic analysis, financial analysis, consulting, or engineering.

Nice To Haves

Graduate degree in statistics, data science, or related field.
Hands-on experience with SQL and Python for big data analysis.

Responsibilities

Analyze large, complex datasets to develop, validate, and enhance predictive models using statistical and machine learning techniques.
Incorporate new data sources (e.g., customer interest metrics, web clickstream, market pricing) to improve model accuracy and performance.
Design and execute controlled experiments to measure the business impact of new models.
Present actionable insights and recommendations to senior leadership to influence strategic decisions.
Research emerging methodologies and best practices to advance CarMax’s modeling capabilities.
Shape the team’s strategic roadmap for data science innovation and communicate model functionality to technical and non-technical audiences.