Machine Intelligence Analyst- P&HVAC

Summary

Sunbelt Rentals, Inc. is a leading company in the equipment rental industry, seeking a Machine Intelligence Analyst to enhance the performance and efficiency of heavy equipment. The role involves utilizing advanced data analysis and machine learning to automate reporting and predictive maintenance, ultimately driving operational optimization.

Responsibilities

• Predictive Maintenance & Diagnostics: Analyze sensor data (vibration, temperature, hydraulic pressure) to predict equipment failure, reducing downtime and lowering maintenance costs
• Telematics & Data Engineering: Extract, clean, and analyze raw data from CAN bus, Modbus, and GPS systems to monitor fleet health and location in real time
• Performance Optimization: Develop AI/ML models to improve fuel efficiency and optimize workflows (e.g., automated scheduling)
• Automated Alerting & Reporting: Create automated dashboards and proactive alerts for operators/managers regarding abnormal machine behavior
• Operational Safety: Utilize ML to identify unsafe operator behavior (e.g., sudden braking, excessive idling) and ensure compliance with regulatory standards

Skills

• Bachelor's degree in data science, Engineering, Computer Science, or a related field
• Strong problem-solving mindset and the ability to communicate technical findings to non-technical stakeholders, such as fleet managers and maintenance crews
• Develop and refine AI/ML models to identify anomalies in equipment performance (e.g., vibration spikes, temperature fluctuations) to predict failures before they occur
• Analyze machine utilization and idle time to recommend better asset allocation and reduce unnecessary operational costs
• Use AI to flag risky operator behaviors—such as harsh braking or overloading—and automate reporting for regulatory standards like OSHA
• Monitor consumption patterns and identify inefficient operating habits to drive fuel savings, often targeting reductions of up to 15%
• Build and maintain dashboards that provide real-time alerts for critical issues like engine faults or unauthorized equipment movement (geo-fencing)
• Experience with industrial communication protocols such as CAN bus and Modbus to collect data from machine control systems
• Proficiency in Python or R, along with libraries like TensorFlow, PyTorch, or Scikit-learn for building predictive models
• Strong understanding of GPS technology, onboard diagnostics (OBD), and Telematics Control Units (TCU) for remote monitoring
• Skills in SQL, data cleaning, and big data tools (e.g., Hadoop, Apache Spark) to handle large volumes of sensor data
• Ability to create complex queries and interactive dashboards using tools like Power BI, Tableau, or specialized construction software
• Advanced degrees are often preferred for senior analyst roles
• Prior experience in the heavy civil construction or mining industries is highly desirable to understand specific machine behaviors and job site logic

Qualifications

Must Haves

• Bachelor's degree in data science, Engineering, Computer Science, or a related field
• Strong problem-solving mindset and the ability to communicate technical findings to non-technical stakeholders, such as fleet managers and maintenance crews
• Develop and refine AI/ML models to identify anomalies in equipment performance (e.g., vibration spikes, temperature fluctuations) to predict failures before they occur
• Analyze machine utilization and idle time to recommend better asset allocation and reduce unnecessary operational costs
• Use AI to flag risky operator behaviors—such as harsh braking or overloading—and automate reporting for regulatory standards like OSHA
• Monitor consumption patterns and identify inefficient operating habits to drive fuel savings, often targeting reductions of up to 15%
• Build and maintain dashboards that provide real-time alerts for critical issues like engine faults or unauthorized equipment movement (geo-fencing)
• Experience with industrial communication protocols such as CAN bus and Modbus to collect data from machine control systems
• Proficiency in Python or R, along with libraries like TensorFlow, PyTorch, or Scikit-learn for building predictive models
• Strong understanding of GPS technology, onboard diagnostics (OBD), and Telematics Control Units (TCU) for remote monitoring
• Skills in SQL, data cleaning, and big data tools (e.g., Hadoop, Apache Spark) to handle large volumes of sensor data
• Ability to create complex queries and interactive dashboards using tools like Power BI, Tableau, or specialized construction software

Nice to Haves

• Advanced degrees are often preferred for senior analyst roles
• Prior experience in the heavy civil construction or mining industries is highly desirable to understand specific machine behaviors and job site logic

Benefits

• Health, Dental and Vision plans
• 401(k) Match
• Volunteer time off
• Short-term and long-term disability
• Accident, Life and Travel insurance, as well as flexible spending
• Tuition Reimbursement Options
• Employee Assistance Program (EAP)
• Length of Service Awards
• You will become eligible for benefits on the first of the month following 30 days from your start date.
• 12-25 vacation days depending on years of service
• 5 sick days
• 6 holidays
• 2 half day holidays
• 2 floating holidays
• 1 inclusion day
• 1 volunteer day