Predictive Analytics Engineer

Job description

SUMMARY

Vertiv is hiring a Data Analyst in Westerville, Ohio to deliver Predictive Analytic Health Score data for Vertiv UPS and Thermal systems. This role will analyze equipment service history, equipment operation and performance, site and environmental conditions, and equipment data acquisition to identify risks and proactively transition emergency repairs into scheduled maintenance. The successful candidate will leverage advanced data analytics, field feedback, and cross-functional collaboration to improve predictive accuracy, mature incident reporting capabilities, and drive operational efficiency across a large-scale asset base.

RESPONSIBILITIES

Collaborate with cross-functional teams to design and deliver dynamic equipment health scorecards with criticality tiers, providing real-time fleetwide visibility and actionable insights. Validate Next Predict incidents with field results to continuously refine algorithms, strengthen machine learning models, and maximize the tool’s predictive accuracy and operational value. Serve as the bridge between the Next Predict Team and Field Operations to enhance tool functionality, improve incident reporting quality, and ensure a closed-loop feedback process from detection to field resolution.

Advance the predictive platform toward delivering fully automated incidents with precise, technician-ready corrective action plans. Develop and deploy analytics solutions —including Python scripts, SQL queries, and Tableau dashboards—to accelerate data processing, increase detection precision, and identify issues before they escalate. Analyze operational trends and escalate systemic issues to subject matter experts, driving swift remediation and long-term reliability improvements.

Partner with Engineering and product teams to integrate smart technologies—advanced sensors, vibration monitoring, and environmental tracking—into Vertiv products, enriching Next Predict data streams and enabling continuous model improvement. Enhance predictive algorithms through simulation models that forecast maintenance needs and optimize asset lifecycle performance. Lead customer and stakeholder reviews to present findings, recommend containment actions, and showcase platform enhancements.

Curate and expand a living knowledgebase of system symptoms, root causes, and best-practice corrective actions to strengthen machine learning outcomes. Report program updates and performance metrics to management, highlighting optimization wins and capability growth opportunities. Travel occasionally to support field validations, training, and platform deployment.

QUALIFICATIONS

Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or Mathematics (Master’s degree and/or Professional Engineer certification preferred). Minimum five years of data center critical power or thermal experience, with demonstrated success in predictive maintenance and system optimization. Proficiency in investigative and data analysis techniques, including large-scale telemetry analysis and automation. Strong programming and analytics skills (Python, SQL, Tableau, Excel) with experience creating tools to improve efficiency and data quality.

Excellent communication skills for both technical and executive audiences, with proven ability to work between engineering teams and field technicians. Strong analytical, organizational, and time management skills; able to manage multiple complex projects simultaneously. Knowledge of quality system processes such as FMEA and Six Sigma, with experience applying energy efficiency standards (e.g., ASHRAE). Self-motivated, adaptable, and effective in fast-paced, reactive environments.

Proficient in Microsoft Office and web-based technologies.