Senior Data Scientist

<div class="content-intro"><p><strong>Who we are</strong></p> <p>At CarGurus (NASDAQ: CARG), our mission is to give people the power to reach their destination. We started as a small team of developers determined to bring trust and transparency to car shopping. Since then, our history of innovation and go-to-market acceleration has driven industry-leading growth. In fact, we’re the largest and fastest-growing automotive marketplace, and we’ve been profitable for over 15 years.</p> <p><strong>What we do</strong></p> <p>The market is evolving, and we are too, moving the entire automotive journey online and guiding our customers through every step. That includes everything from the sale of an old car to the financing, purchase, and delivery of a new one. Today, tens of millions of consumers visit CarGurus.com each month, and ~30,000 dealerships use our products. But they're not the only ones who love CarGurus—our employees do, too. We have a people-first culture that fosters kindness, collaboration, and innovation, and empowers our Gurus with tools to fuel their career growth. Disrupting a trillion-dollar industry requires fresh and diverse perspectives. Come join us for the ride!</p></div><p><strong>Role overview</strong></p> <p>As a member of the Data Science team with a focus on CarGurus’s international products, the Senior Data Scientist, International will be responsible for implementing, training and testing machine learning models in support of CarGurus’s fastest growing markets in the UK and Canada. Potential areas of support and ownership include Search Ranking, Recommendations, and Instant Market Value algorithms.</p> <p><strong>What you'll do</strong></p> <ul> <li>Partner with product and engineering teams in CarGurus UK and Canada to understand their product requirements and data assets</li> <li>Implement, train, and evaluate machine learning models using Python and AWS SageMaker.</li> <li>Develop and maintain data pipelines to supply training and inference data for models, using SQL and Snowflake.</li> <li>Collaborate with engineers to deploy models to production</li> <li>Evaluate performance of production-deployed models</li> <li>Design A/B tests of the Data Science team’s models and analyze their results</li> <li>Communicate solutions to stakeholders through written documentation, demos and presentations, and data visualizations</li> <li>Collaborate with other data scientists, machine learning engineers, and business stakeholders to scope, design, and implement machine learning projects</li> </ul> <p><strong>What you'll bring</strong></p> <ul> <li>Curiosity about widely varied datasets and their possibilities for unlocking custome