J.D. Power-posted 7 days ago
Full-time • Mid Level
Remote

As part of the Data and Analytics division of JD Power, you will work to understand the features that drive the price of a vehicle and predict what future vehicle values will be, and other critical insights for the sector. Our data science team is accountable for every data point we output and provides accurate, transparent, industry-leading analytics. We are looking for an Data Scientist who will have the freedom to utilize the latest technologies to solve challenging problems, create innovative machine learning processes from the ground up, deploy them into production. We are a mature and tight-knit data science team looking to add another top-shelf team member who is ready to make a difference in the automotive industry. Join us! About the Job: Daily immersion in automotive industry data Leading end-to-end data science projects. Designing and implementing complex feature engineering strategies. Building and deploying advanced AI/ML and classical regression models. Conducting advanced model evaluation and optimization. Documentation of machine learning processes Involves leading and managing complex end-to-end data science projects. Requires expertise in designing intricate feature engineering strategies. Collaborate closely with technology and engineering teams to improve existing processes and build out new ones Work with the product team to develop the analytics that will power new products Expertise in advanced feature engineering and AI/ML model building. Mastery of SQL, Python, and Advanced Excel for advanced data manipulation. In-depth knowledge of AWS SageMaker, Palantir Data Science Integrations or other Machine Learning frameworks. Create visual reports for internal and external clients that summarize findings Team environment that encourages the sharing of ideas to build the best predictive algorithms Ad-hoc data analysis and reporting

  • Daily immersion in automotive industry data
  • Leading end-to-end data science projects.
  • Designing and implementing complex feature engineering strategies.
  • Building and deploying advanced AI/ML and classical regression models.
  • Conducting advanced model evaluation and optimization.
  • Documentation of machine learning processes
  • Involves leading and managing complex end-to-end data science projects.
  • Requires expertise in designing intricate feature engineering strategies.
  • Collaborate closely with technology and engineering teams to improve existing processes and build out new ones
  • Work with the product team to develop the analytics that will power new products
  • Create visual reports for internal and external clients that summarize findings
  • Team environment that encourages the sharing of ideas to build the best predictive algorithms
  • Ad-hoc data analysis and reporting
  • Demonstrated expertise with data analytics and/or statistical concepts such as: regression, logistic regression, time-series modeling, Bayesian statistics, machine learning, data mining, simulation, optimization, and/or forecasting
  • Ability to communicate technical processes to a lay audience
  • Presentation experience
  • Curiosity and passion for solving problems with data
  • 4+ years of professional experience working with large datasets
  • 4+ years of professional experience and fluency with statistical programming software, especially Python and Spark
  • 4+ years of professional experience with database software (RedShift, Hive, SQL, MYSQL) – strong SQL skills
  • Master’s Degree in Statistics, Data Science, Economics, or a related technical field
  • Expertise in advanced feature engineering and AI/ML model building.
  • Mastery of SQL, Python, and Advanced Excel for advanced data manipulation.
  • In-depth knowledge of AWS SageMaker, Palantir Data Science Integrations or other Machine Learning frameworks.
  • Experience with automotive market data
  • Professional expertise deploying cloud-based ML Ops systems
  • Experience working with AWS tools (Sagemaker, Glue, Batch, Lamdba…)
  • Some shareable examples of data visualizations you have created
  • Experience deploying machine learning models into production with an API
  • PhD in Statistics, Data Science, Economics, or related field
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