Sr. Data Scientist - Pricing Algorithms
CarMax View all jobs
- Richmond, BC
- Permanent
- Full-time
- Do the Right Thing: We prioritize maintaining the culture of integrity which has set CarMax apart in the used car industry, and promote a respectful and inclusive environment at work
- Put People First: We’re focused on nurturing associate development and on maintaining a healthy work culture, while also making sure our customers are offered a great experience
- Win Together: Teamwork is essential to what we do; we regularly learn from each other and draw on each other’s expertise and perspectives
- Go for Greatness: We continually improve our abilities and the products that we support, to build up CarMax’s position as an industry leader
- Interpret, validate, and apply feature engineering to large and complex pricing-related data sets
- Find creative ways to incorporate new insights and data sources
- Leverage statistical / machine learning techniques and sound reasoning to develop, validate, and improve predictive models
- Design controlled experiments to assess the business value of new models
- Present insights and recommendations to senior leaders to drive change
- Research innovations and best practices related to data sources, modeling methodologies, and data science tools
- Influence the team in the development of our modeling capability strategic roadmap
- Either a bachelor’s degree in a quantitative discipline OR equivalent experience and training through past employment
- At least 2 years relevant work experience (Advanced study in a quantitative field may substitute for work experience), including experience applying strong foundational math and/or modeling skills to solve complex problems
- Extracting and sharing clear insights from modelling
- Project management, ideally including end-to-end experience with the machine learning deployment pipeline
- Relationship building and collaboration
- Expertise in selecting and applying various modeling techniques (supervised & unsupervised, classification & regression, etc.),
- Python/SQL programming
- Data cleaning and pre-processing
- Statistical and probabilistic analysis