Data Science Manager, Personalization. Richmond LilyLifestyle

8901 - Corp Office West Crk - 12800 Tuckahoe Creek Parkway, Richmond, Virginia, 23238

The Person alization 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.

Vehicle Recommender is our team's marquee data science product - a full-scale, modern software solution built on a custom embedding model. Launched in 2024 to replace our legacy system, it delivers intelligent, real-time, customizable product recommendations across our retail and wholesale businesses. We're looking for a data scientist who wants to own a product, not just build models. In this role, you'll develop deep technical expertise in our recommender system, but you'll spend just as much time working with partners across the business - understanding their needs, scoping use cases, advocating for adoption, and ensuring we deliver real value.

To be clear: this is a data scientist role, not a product manager role. You'll still be hands-on with data, experimentation, and model evaluation. But if you're the kind of DS who lights up in a roadmap discussion, loves translating ML capabilities into business terms, and wants to be the go-to expert that partners come to - this is your role.

This role may or may not initially include direct reports, but that can depend on the individual candidate. It's ideal for an experienced data scientist interested in growing toward technical leadership or product-oriented career paths.

Serve as the primary point of contact for Vehicle Recommender across the organization - owning relationships with product managers, business stakeholders, and engineering partners

Drive adoption by helping partners understand what recommendations can do for them, scoping new use cases, and ensuring successful implementation

Own the roadmap for Vehicle Recommender in partnership with engineering and DS leadership - prioritizing enhancements, maintenance, and new capabilities

Translate between technical and business audiences; present to leadership, write strategy docs, and make the case for investment

Develop deep technical expertise in the Vehicle Recommender system - how the embedding models work, how recommendations are generated and served, and how performance is measured

Design, execute, and interpret experiments (A/B tests, holdouts, pre/post analyses) to quantify impact and guide decisions

Partner with data scientists and engineers on feature development, model validation, and system monitoring

Stay current on recommender system research and best practices; bring informed perspective to technical decisions

5+ years of experience in a data science role, preferably in e-commerce, marketplace, or a data-rich environment

Strong development skills and experience with Python for data manipulation, analysis, and model development

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

Clear communication skills - you can explain a complex analysis to a PM or executive without losing them, and present a compelling argument for how and why a team will benefit from using recommendations

Genuine enthusiasm for how search and recommendation systems work and passion for continued learning

Bachelor's degree in a quantitative field (statistics, economics, math, engineering, or similar)

Advanced degree (Master's/Ph.D.) is preferred

Work Authorization:
Applicants must be currently authorized to work in the United States on a full-time basis. Sponsorship will not be considered for this specific role.

Car Max is committed to bringing together people from different backgrounds and perspectives, providing employees with a safe, welcoming, and inclusive work environment.

Car Max is an equal opportunity employer, and all qualified candidates will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, gender expression, genetic information, national origin, protected veteran status, disability status, and any other characteristics protected by law.

Upon an applicant's request, Car Max will consider reasonable accommodation to complete the Car Max Job Application.