Manager of Data Science, Personalization

About this job

It’s an exciting time at Car Max! After decades of success and a rise to becoming the largest used car retailer in the US, Car Max is focused on disrupting the auto industry once again through our transformation to a leading omni‑channel retailer. To achieve this goal, Car Max has spent the last few years investing heavily in modernizing our digital and analytical infrastructure to support our customer‑centric experience as the customer shopping journey continues to evolve online.

We’re stitching data science throughout our business to drive a great customer experience and optimize our operations.

As a Data Science Manager at Car Max, you’ll apply your passion and expertise for data, machine learning, predictive analytics, and entrepreneurship to create data‑powered products that enrich Car Max’s culture of innovation and drive business results. You will be a leader in the analytic community – advancing the use of data science in high‑impact areas of our business.

With millions of customer interactions every day, and thousands of unique vehicles in inventory, you’ll be tapping the industry’s best data to develop new algorithms and personalized experiences that help customers efficiently find the right car and navigate their car‑buying journey.

• Collaborate with Product teams across Car Max to explore new use cases for our Production‑grade Recommendations Service, expanding across digital and physical customer touchpoints.
• Lead the end‑to‑end experimentation lifecycle for Personalization initiatives
  , from hypothesis generation through A/B test design, analysis, and deployment. You will partner with Product and Strategy teams to identify and prioritize testing opportunities to drive key business metrics like vehicle reservation leads and sales conversion.
• Evolve architectural solutions that reflect the unique challenges at Car Max: the length of our customers’ consideration phase, the complexity of an omnichannel journey, and the need to balance customer discovery with inventory constraints.
• Drive technical innovation and maintain industry awareness of best‑in‑class recommender systems, personalization techniques, and use of emerging AI. Research and implement relevant approaches – including contextual bandits, two‑tower architecture, and next‑generation personalization paradigms like LLM integration – to continuously advance Car Max’s capabilities and ensure we leverage state‑of‑the‑art approaches that deliver business value.

• Advanced Degree (Master’s/Ph.D.) in quantitative discipline (Statistics, Math, Data Science, Engineering) is preferred.
• 3+ years of experience in the following areas:
  • R, Python, Scala, or other languages appropriate for large scale analysis of numerical and textual data
  • Data mining, machine learning, statistical modeling tools and underlying algorithms
  • Data Lake and cloud computing fundamentals
• Strong analytical curiosity and passion for applying advanced modeling techniques in problem solving.
• Sound analytical thinker with a proven track record of providing actionable insights and clear strategic direction.
• Ability to convey complex, technical subject matter in a clear and straightforward manner; demonstrated ability to effectively communicate through written and oral presentations with all levels of the organization.
• Solid project management skills with the ability to juggle multiple priorities simultaneously in a fast‑paced environment.
• Ability to train and mentor others.
• Experience in Recommender Systems, Search Algorithms, or operationalizing performant algorithms for website integration is a plus.

• Experience building and scaling production recommendation systems in retail, e‑commerce or marketplace environments.
• Hands‑on expertise with modern recommender architectures including embedding models, retrieval systems, and rerankers.
• Deep understanding of MLOps practices.
• Experience with large‑scale A/B test design and analysis.
• Experience with real‑time or near‑real‑time inference systems and managing latency/throughput tradeoffs at scale.
• Familiarity with complex products requiring nuanced…