JD Power is looking for an AI Engineer to understand vehicle pricing drivers and predict future vehicle values, creating innovative machine learning processes and deploying them into production to solve problems in the auto industry and impact core products for clients.
Requirements
- Demonstrated proficiency of AI programming languages including Python.
- Demonstrated use of AI evaluation metrics including accuracy, precision, recall, ROC, AUC, F1 scores, MSE, R-squared, etc, in model building & evaluation.
- 8+ years of professional experience working with large datasets
- 8+ years of professional experience with statistical programming software (Spark, Python preferred)
- 10+ years of professional experience and fluency with database software (RedShift, Hive, SQL, MYSQL)
- 5+ years of professional experience deploying cloud-based automated analytic processes
- 5+ in machine learning model deployment with automate model monitoring
Responsibilities
- Create reusable frameworks to integrate multiple AI models into production workflows.
- Lead the creation of multiple AI models simultaneously and put them into production.
- Coach team members on exploratory data analysis, feature engineering, and data transformations.
- Build models that go into production and directly impact our core products for our clients.
- Build models, deploy them in the cloud, and build monitoring suites leveraging industry-standard tools.
- Utilize the latest technologies to solve challenging problems.
- Create innovative machine learning processes from the ground up, deploy them into production on our AWS server and/or Palantir, and develop cutting-edge tools for monitoring our ML suite of algorithms.
Other
- Experience daily immersion in automotive industry data.
- Working with business units to articulate a pipeline of AI projects to drive operational efficiency and revenue growth.
- Communications to customer success, product, and senior data science leadership while requiring minimal feedback for communication documents and presentations.
- Leads PI (Program Increment) planning for activities to be conducted in the next quarter, with limited supervision, for major developmental modules or projects.
- Fluent in other data science models, data sources, and data limitations within business units.
