Senior Analyst, Search and Recommendations

CarMax • Nampa, ID

10d

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 deep expertise about our business through data: via ad-hoc analysis, supporting ML model development and management, and especially through the design and execution of rigorous statistical tests that help us understand what's actually working and what’s not. You'll be embedded with data scientists and ML engineers, which means you'll see how models are built, not just how they perform. You'll help shape what we test, how we measure success, and what we learn. If you love data, get excited about the mechanics of search and recommendations, and want to see your analysis directly influence product decisions, this role is for you.

Requirements

• 3+ years of experience in an analytical role, preferably in e-commerce, marketplace, or another data-rich environment
• Strong SQL skills and experience with Python (e.g. pandas, matplotlib) for data manipulation and analysis
• 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 is preferred
• Ability to build and maintain reports in BI tools (Tableau, PowerBI, Looker, etc.), or interest in learning
• Clear communication skills - you can explain a complex analysis to a product manager or executive without losing them
• Genuine enthusiasm for how search and recommendation systems work, even if you haven't built them yourself
• Bachelor's degree in a quantitative field (statistics, economics, math, engineering, or similar)

Responsibilities

• 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 data scientists on model development, validation, and ongoing monitoring - acting as a bridge between model performance metrics and business outcomes
• Translate complex findings into clear narratives for technical and non-technical stakeholders alike
• Develop and maintain dashboards and reporting that help the team and partners track key metrics over time
• Partner closely with cross functional teams in Product, Strategy, Technology, and Operations

What This Job Offers

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