Lead Data Scientist (service Events & Insights)

Caterpillar Caterpillar · Industrial · Peoria, IL

Lead Data Scientist role focused on developing advanced analytics and machine learning models for service events and insights within Caterpillar's Product Support and Logistics Division. The role involves translating large-scale service data into actionable business insights, applying techniques like NLP and predictive modeling, and optimizing model performance. The goal is to improve service outcomes, forecasting, and decision-making accuracy.

What you'd actually do

  1. Leading the design and execution of advanced analytics and data science initiatives, translating large-scale Service Events data into actionable business insights
  2. Directing data acquisition, transformation, and modeling efforts across complex, high-volume datasets to enable scalable and reliable analytics solutions
  3. Defining problem statements, analytical approaches, and success criteria in collaboration with business stakeholders to ensure alignment with strategic objectives
  4. Developing, deploying, and optimizing machine learning models and statistical analyses to improve service outcomes, forecasting, and decision-making accuracy
  5. Applying advanced techniques such as natural language processing, text analytics, and predictive modeling to extract value from structured and unstructured service data

Skills

Required

  • Accuracy and Attention to Detail
  • Analytical Thinking
  • Machine Learning
  • Programming Languages
  • Business Statistics
  • Query and Database Access Tools

Nice to have

  • 4-year college degree in Business, Engineering, Data Science, Mathematics, or a related field, or equivalent experience
  • Deep expertise in statistical analysis and machine learning techniques, with the ability to apply advanced methodologies to solve complex business problems
  • Strong proficiency in programming languages (e.g., Python, R, SQL) and data processing frameworks, with experience developing and productionizing analytical solutions
  • Advanced knowledge of data modeling, database systems, and query optimization, including experience working with large-scale, distributed datasets
  • Demonstrated ability to lead end-to-end machine learning initiatives, including model selection, training, evaluation, and performance monitoring
  • Proven expertise in translating complex analytical findings into clear, actionable insights for both technical and non-technical audiences
  • Strong analytical thinking and problem-solving capabilities, including the ability to decompose complex challenges and evaluate multiple solution paths
  • Experience with Service Events Domain data, including dealer Work Orders, SMCS hierarchies, service response, fluid sampling, inspection, and Cat Interact t

What the JD emphasized

  • Machine Learning
  • Programming Languages
  • Business Statistics
  • Query and Database Access Tools
  • statistical analysis and machine learning techniques
  • programming languages (e.g., Python, R, SQL)
  • data modeling, database systems, and query optimization
  • end-to-end machine learning initiatives

Other signals

  • Develop, deploy, and optimize machine learning models
  • Applying advanced techniques such as natural language processing, text analytics, and predictive modeling
  • Lead investigation into data model optimization, algorithm performance, and analytical methodologies