1,211 open roles
Senior Manager, Data Science
$139k to $222k
Against the Richmond typical range
Job description
8116
- Midtown Office - 2220 W. Broad Street, Richmond, Virginia, 23220 Car. Max, the way your career should be! Technical Leadership & Execution Lead the development and enhancement of predictive Customer Progression models Apply advanced data science techniques across the full model lifecycle: Design, training, evaluation, validation, deployment, and monitoring Analyze large-scale, complex datasets (customer, transactional, digital, and third-party data) to generate actionable insights Build deep understanding of Car. Max data ecosystems, including data access, processing, and monitoring Design and support controlled experiments (A/B testing) to evaluate new solutions Cross-Functional Collaboration Partner with Product, Operations, Strategy, and Data Engineering teams to: Identify and develop new use cases for data-driven products Deliver tools that enhance both the customer and associate experience Build scalable data and modeling infrastructure Communicate insights, model outcomes, and opportunities clearly to stakeholders at all levels of the organization Influence business strategy through data-driven recommendations Team Leadership & Development Lead, mentor, and develop a high-performing team of data scientists Promote best practices in analytics, modeling, and experimentation Manage and prioritize multiple projects in a fast-paced environment Foster both technical and professional growth within the team Qualifications Required Advanced degree (Master’s or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Data Science, Computer Science, or Engineering 4+ years of experience in: Python or similar languages for large-scale data analysis Machine learning, statistical modeling, and data mining techniques Working with data lakes, cloud platforms, and relational databases (SQL) Strong analytical mindset with a proven track record of delivering insights and strategic impact Excellent communication skills with the ability to explain complex concepts to both technical and non-technical audiences Demonstrated project management skills and ability to manage competing priorities Experience mentoring or developing team members Preferred Hands-on experience developing and deploying NLP (Natural Language Processing) solutions, including: Information retrieval and extraction Sentiment analysis Topic modeling Classification and deep learning techniques Work Location and Arrangement This role will be based out of the Car. Max Technology Innovation Center (Richmond, VA) and associates will work onsite 4 days per week. 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. The annual salary for this position is: $138,500.00 - $221,600.00 May be eligible for bonus and equity.
Benefits
Except as otherwise required by state law, Car. Max Associates are entitled to the following paid sick, vacation, and holiday time. Associates that are considered full-time hourly or commission/incentive eligible: To earn up to 48 hours of sick time per year accrued on a per pay period basis and between 80 hours and 200 hours per year of vacation time after a 90 day waiting period depending on years of continuous service with the Company.
For 8 hours of pay for each of a total of 6 paid scheduled holidays per year plus 1 floating holiday. If such an Associate does work on a scheduled holiday due to business need, they are eligible for Holiday Premium Pay. Associates considered full-time salaried are entitled to paid time away with no specified limit as needed for sick, vacation, bereavement, jury duty, holidays, floating holiday, etc.
subject to manager approval. For more details about benefits, please visit our Car. Max Benefits website. Upon an applicant's request, Car. Max will consider reasonable accommodation to complete the Car. Max Job Application .
Description copied from CarMax's careers page. Read the full posting before you apply.
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