Senior Data Scientist, Search and Recommendations

CarMax • Nampa, ID

17d • Hybrid

About The Position

About The Team The Personalization data science team builds and maintains search algorithms and recommender systems that are at the forefront of creating a modern, engaging, digital shopping experience for our customers. We see millions of customers every week across web and mobile. We deploy custom deep learning embedding models, ranking and segmentation algorithms, and are constantly testing new approaches. Our systems are used in dozens of product use cases across the retail and wholesale businesses, which means we partner with many diverse teams throughout the organization. About The Role Understanding our business - the used vehicle market, our customers, and our digital products - is at the heart of what we do on this team. Our data is massive, rich, and often challenging to work with. In this role you will develop and maintain ML models that deliver a highly personalized experience for our customers, driving measurable impact to critical business metrics such as online engagement, lead initiation, and sales. You will also design and execute rigorous statistical tests that allow us to measure these impacts and optimize our systems. You'll work side by side with ML engineers on model deployments and service design, which means you'll be part of the end-to-end ML lifecycle and not just stuck in notebooks. If you love data and get excited about search and recommender algorithms, this role is for you.

Requirements

• 3+ years of experience in a data science role, preferably in e-commerce, marketplace, or a data-rich environment
• Degree in quantitative discipline field such as math, data science, statistics, computer science
• Strong Python skills and experience with SQL for data manipulation, analysis, and model development, as well as foundational software development experience
• Solid foundation in statistics, including hypothesis testing, confidence intervals, and experimental design - you should be comfortable explaining why a test result is or isn't significant
• Experience working with large datasets using tools like Spark, Databricks, or similar
• Comfort with ambiguity and ability to drive clarity when requirements are fuzzy
• Collaborative mindset—you enjoy working with engineers, PMs, and analysts, not just other data scientists

Nice To Haves

• Advanced degree (Master’s/Ph.D.) is preferred
• Experience with recommender systems, search/ranking algorithms, or embeddings is a plus—but if you haven't worked on these yet and are eager to learn, we'll get you there

Responsibilities

• Design, develop, deploy, and maintain ML products that create personalized experiences for our customers
• Analyze large-scale behavioral data (search queries, click-through rates, purchase patterns, inventory turnover) to surface insights about customer preferences and system performance
• Design, execute, and interpret statistical tests (A/B tests, holdout experiments, pre/post analyses) to measure the impact of algorithm changes and new features
• Partner with ML engineers on model deployment and ML product development (API’s, data services, etc.)
• Translate complex data and ML findings into clear narratives for technical and non-technical stakeholders alike
• Partner closely with cross functional teams in Product, Strategy, Technology, and Operations
• Stay current on research and best practices in recommender systems and search; bring new ideas to the team

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level