Data Science/analyst

Caterpillar Caterpillar · Industrial · Chicago, IL +2

This role focuses on building AI and analytics solutions for Caterpillar customers, involving machine learning, Generative AI, and IoT data. The responsibilities include developing predictive models for equipment failure, utilizing Generative AI for solutions, prompt engineering, fine-tuning AI models, and creating agents/assistants/chatbots. The role also involves evaluating emerging technologies and ensuring connectivity through telematics. It is an entry-level to mid-level position in the industrial domain.

What you'd actually do

  1. Develop models to power asset management solutions for customers and dealers using machine learning, deep learning, and statistics-based/physics-based analytics techniques on time-series sensor data, machine fault codes, inspections and analysis records to identify health anomalies, predict equipment failure modes, estimate remaining useful life, and build equipment risk models
  2. Evaluating emerging technologies by evaluating new product services and technology platforms
  3. Utilize Generative AI to develop and implement solutions, encompassing model training, evaluation, and selection. Engage in Prompt Engineering by fine-tuning AI models, developing new models, creating agents, assistants, and chatbots
  4. Ensure long-term connectivity through strategic planning and execution, including global telematics device programs. This involves testing, research, and analysis of cellular, satellite, Wi-Fi, Bluetooth, and other on-board and off-board technologies
  5. Provide digital technical support for essential Caterpillar digital applications and products

Skills

Required

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

Nice to have

  • Python
  • SQL
  • Cloud Platforms
  • Data Visualization Tools
  • IoT & Telematics Data
  • Statistical Modeling
  • Bachelor’s degree or higher in data science, computer engineering, electrical engineering or related degree
  • 0-2 years of relevant experience
  • Minimum cumulative GPA requirement 3.0/ 4.0
  • Experience through internships, personal projects, research, hackathons, student organizations, or coursework

What the JD emphasized

  • machine learning
  • Generative AI
  • predict equipment failure
  • model training
  • evaluation
  • selection
  • Prompt Engineering
  • fine-tuning AI models
  • developing new models
  • creating agents
  • assistants
  • chatbots

Other signals

  • Develop models to power asset management solutions
  • Utilize Generative AI to develop and implement solutions
  • Engage in Prompt Engineering by fine-tuning AI models, developing new models, creating agents, assistants, and chatbots