Senior Data Scientist
Headquartered in Cambridge, Massachusetts, CarGurus is the all-in-one platform that’s moving the entire car shopping journey online and guiding customers through each step. This includes everything from selling an old car to financing, purchasing, and delivering a new one. Today, millions of consumers visit cargurus.com each month, and more than 30,000 dealerships use our products. We have a people-first culture that fosters kindness, collaboration, and innovation, while empowering our Gurus with tools and resources to fuel their career growth. Our goal is to give all people—consumers, dealers, and our employees—the power to reach their destination.
Job Description
Role overview
As a core member of the Data Science team, the Senior Data Scientist will be responsible for implementing and training machine learning models, developing and maintaining data pipelines to supply training and inference data for models, evaluating performance of production-deployed models, and supporting A/B testing of the Data Science team’s models. Potential areas of support and ownership include Recommendations, Search Ranking, and Instant Market Value algorithms.
What you'll do
- Implementing, training, and evaluating machine learning models using Python and AWS SageMaker.
- Developing and maintaining data pipelines to supply training and inference data for models, using SQL and Snowflake.
- Collaborating with engineers to deploy models to production
- Evaluating performance of production-deployed models
- Designing A/B tests of the Data Science team’s models and analyzing their results
- Communicating solutions to stakeholders through written documentation, demos and presentations, and data visualizations
- Collaborating with other data scientists, machine learning engineers, and business stakeholders to scope, design, and implement machine learning projects
What you'll bring
- Curiosity about widely varied datasets and their possibilities for unlocking customer value. Self-motivated to perform exploratory analyses and build proof-of-concept solutions.
- Proven experience turning data into successful products
- Knowledge of standard Machine Learning techniques for supervised and unsupervised learning across structured and unstructured datasets. Comprehensive knowledge of, and real-world experience with, measurement, evaluation, and testing of models.
- Experience deploying and/or maintaining machine learning services in production
- Proficiency in Python or similar languages widely used in the data science community
- Proficiency in SQL
- Ability to communicate technical details and analytical findings to both technical and non-technical audiences
- Advanced degree (or proven experience) in Computer Science, Data Science, Mathematics, or any quantitative science which makes use of advanced data analytics or statistical or machine learning techniques
Role overview
As a core member of the Data Science team, the Senior Data Scientist will be responsible for implementing and training machine learning models, developing and maintaining data pipelines to supply training and inference data for models, evaluating performance of production-deployed models, and supporting A/B testing of the Data Science team’s models. Potential areas of support and ownership include Recommendations, Search Ranking, and Instant Market Value algorithms.
What you'll do
- Implementing, training, and evaluating machine learning models using Python and AWS SageMaker.
- Developing and maintaining data pipelines to supply training and inference data for models, using SQL and Snowflake.
- Collaborating with engineers to deploy models to production
- Evaluating performance of production-deployed models
- Designing A/B tests of the Data Science team’s models and analyzing their results
- Communicating solutions to stakeholders through written documentation, demos and presentations, and data visualizations
- Collaborating with other data scientists, machine learning engineers, and business stakeholders to scope, design, and implement machine learning projects
What you'll bring
- Curiosity about widely varied datasets and their possibilities for unlocking customer value. Self-motivated to perform exploratory analyses and build proof-of-concept solutions.
- Proven experience turning data into successful products
- Knowledge of standard Machine Learning techniques for supervised and unsupervised learning across structured and unstructured datasets. Comprehensive knowledge of, and real-world experience with, measurement, evaluation, and testing of models.
- Experience deploying and/or maintaining machine learning services in production
- Proficiency in Python or similar languages widely used in the data science community
- Proficiency in SQL
- Ability to communicate technical details and analytical findings to both technical and non-technical audiences
- Advanced degree (or proven experience) in Computer Science, Data Science, Mathematics, or any quantitative science which makes use of advanced data analytics or statistical or machine learning techniques
