Machine Intelligence Analyst- P&HVAC

Join Our Team!

Sunbelt Rentals strives to be the customer's first choice in the equipment rental industry. From pumps to scaffolding to general construction tools, we aim to be the only call needed to outfit a job site with the proper equipment. Not only do we offer a vast fleet that ranks among the best in the industry, we pair it all with a friendly and knowledgeable staff.

Our employees are our greatest asset, and although we present a comprehensive equipment offering, our expertise and service are what truly distinguish us from the competition.

We pride ourselves on investing in our workforce and offer competitive benefits, as well as extensive on-the-job training for all eligible employees.

As a highly successful national company, we are constantly looking for talented individuals to support our growth. If you are interested in pursuing a rewarding career, we invite you to review our opportunities!

Position Objective:

A Machine Intelligence Analyst focuses on utilizing advanced data analysis, artificial intelligence (AI), and machine learning (ML) to improve the performance, safety, and efficiency of heavy equipment. This role bridges the gap between raw telematics data—collected from sensors and CAN bus /Modbus systems—and actionable business intelligence by automating reporting and alerting to drive predictive maintenance, fuel savings, and operational optimization.

Position 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.

Requirements:

Education & Experience:

• Bachelor's degree in data science, Engineering, Computer Science, or a related field; advanced degrees are often preferred for senior analyst roles.
• Domain Knowledge:
  Prior experience in the heavy civil construction or mining industries is highly desirable to understand specific machine behaviors and job site logic.
• Soft Skills:
  
  Strong problem-solving mindset and the ability to communicate technical findings to non-technical stakeholders, such as fleet managers and maintenance crews.
• Predictive Maintenance Modeling:
  Develop and refine AI/ML models to identify anomalies in equipment performance (e.g., vibration spikes, temperature fluctuations) to predict failures before they occur.
• Fleet & Operational Optimization:
  Analyze machine utilization and idle time to recommend better asset allocation and reduce unnecessary operational costs.
• Safety & Compliance Monitoring:
  Use AI to flag risky operator behaviors—such as harsh braking or overloading—and automate reporting for regulatory standards like OSHA.
• Fuel Efficiency Analysis:
  Monitor consumption patterns and identify inefficient operating habits to drive fuel savings, often targeting reductions of up to 15%.
• Automated Reporting & Alerting:
  Build and maintain dashboards that provide real-time alerts for critical issues like engine faults or unauthorized equipment movement (geo-fencing).

Essential Technical

Skills:

• Data Integration:
  Experience with industrial communication protocols such as CAN bus and Modbus to collect data from machine control systems.
• AI/ML Frameworks:
  Proficiency in Python or R, along with libraries like Tensor Flow, PyTorch, or Scikit-learn for building predictive models.
• Telematics Expertise:
  Strong understanding of GPS technology, onboard diagnostics (OBD), and Telematics Control Units (TCU) for remote monitoring.
• Data Management:
  Skills in SQL, data cleaning, and big data tools (e.g., Hadoop, Apache Spark) to handle large volumes of…