Validation & Verification engineer – Fleet Data Analytics & Validation
Pubblicato il 10-08-2026 - Iveco Group in Torino
PRIMARY FUNCTION
Responsible for developing and implementing a data-driven fleet monitoring and validation process, leveraging vehicle operational data to support engineering decision-making, system behavior assessment, reliability growth and validation effectiveness.
The role is responsible for transforming fleet operational data into actionable engineering insights through the definition of monitoring strategies, data analytics methodologies, mission-based validation approaches and dashboard solutions supporting validation, reliability and engineering activities.
Working closely with System Validation Engineers and cross-functional engineering teams, the position will define the parameters to be monitored, establish engineering thresholds and performance limits, develop analytical methodologies, and identify vehicle mission profiles that are representative or particularly severe for specific systems and failure modes.
A key objective of the role is to improve the correlation between vehicle validation activities and real-world customer usage by identifying,
quantifying and characterizing operating conditions that can accelerate failure mode validation, increase validation representativeness and support reliability growth activities.
DIMENSIONS
Single contributor, monitoring of approx. 500-800x different vehicles on fleet
ESSENTIAL RESPONSABILITIES
Fleet Data Management & Monitoring
Work closely with System Validation Engineers to identify the relevant vehicle, system and component parameters to be monitored through fleet operational data.
Support the definition of engineering limits, threshold values, warning levels and monitoring criteria required to assess system behavior under real operating conditions.
Define signal requirements, data collection strategies and data quality criteria for fleet monitoring activities.
Develop and maintain automatic data post-processing methodologies, including plausibility checks, event creation, statistical analysis, filtering