Data Analyst at DOC Maintenance LLC

, South Carolina, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Feb, 26

Salary

0.0

Posted On

15 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Predictive Modeling, SQL, Python, Statistical Analysis, Machine Learning, Data Cleaning, Collaboration, Problem Solving, Critical Thinking, Detail Oriented, Adaptability, IoT, Predictive Maintenance, Reliability Engineering, Industrial Equipment

Industry

Facilities Services

Description

Description About the Role: We’re looking for a Data Analyst to support our predictive maintenance initiatives for IoT-enabled equipment. In this role, you’ll analyze historical and real-time equipment data, build predictive models, and turn insights into actionable recommendations that help improve uptime, reduce maintenance costs, and drive smarter operational decisions. What You’ll Do: Extract, clean, and analyze data from IoT-enabled equipment and internal maintenance systems. Retrieve and evaluate historical equipment data to highlight ROI, uptime improvements, and cost savings. Establish baseline failure rates, component lifecycles, and expected runtime or cycle counts between maintenance events. Design, build, and validate statistical and machine learning models to detect anomalies in equipment behavior. Link sensor data with historical service records to uncover correlations between equipment performance and maintenance outcomes. Contribute to the development of “Digital Twin” structures that combine service records and sensor measurements to: Estimate component service life and degradation Track usage trends (e.g., cycle counts, run time) Predict remaining useful life and recommended maintenance schedules Develop predictive dashboards to visualize trends, performance patterns, and potential failures. Partner with Engineering, IT, and Service Operations teams to ensure data accuracy and system connectivity. Translate technical insights into clear, actionable recommendations for business and field teams. What You Bring: Education: Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent practical experience). Technical Skills: Strong proficiency in SQL and time-series databases Programming experience in Python or MATLAB Experience with data cleaning, wrangling, and large “messy” datasets Solid understanding of statistical analysis and modeling Soft Skills: Analytical thinker with strong problem-solving and critical-thinking abilities Excellent communication and collaboration skills Detail-oriented, proactive, and adaptable in a fast-paced environment Preferred Experience: Exposure to industrial equipment, manufacturing, material handling (e.g., forklifts, pallet jacks), or telematics data Experience with predictive maintenance (PdM), reliability engineering, or industrial IoT (IIoT) initiatives Why Join Us: You’ll be part of a growing team driving innovation through data and technology, helping shape the future of equipment reliability and maintenance strategy. This is an opportunity to apply advanced analytics to real-world challenges and make a measurable impact on operational performance. We are an equal opportunity employer and value diversity at all levels of the organization. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Responsibilities

The Data Analyst will analyze historical and real-time equipment data to support predictive maintenance initiatives. They will build predictive models and provide actionable recommendations to improve equipment uptime and reduce maintenance costs.