The Data Scientist will improve service quality and equipment reliability by developing tools and systems for improving workflows and optimising maintenance processes using suitable practices, Reliability Centred Maintenance (RCM), Condition Base Maintenance (CBM) methodology and Data Science Techniques.The Data Scientist will play a critical role in connecting field operations with the maintenance organisation, helping minimise downtime and failure rates and maximise train operation.Responsibilities
Review and design main train subsystems with focus on maintainability, availability, reliability and CBM rule applicationDevelop prognostic algorithms, principles based on its logic, signals/events/operational information within related resolution and sampling timing and prescriptions for maintenanceDevelop models for telemetry/diagnostic streams (e.g., anomaly detection, forecasting, survival/RUL) in Python and SQL, orchestrated on Kubernetes with Kubeflow Pipelines.Analyse diagnostics and maintenance data and create operational dashboards (e.g., Power BI, Grafana) to support maintainers and engineersMonitor prognostic system performances and statistical analysis on collected data to identify critical trends and conditions.Support prognostic algorithm verification and validation. This will include simulations with TCMS simulator and historical diagnostic data, analysis of maintenance reports and on field failures.Study and review of the vehicle FMECA/FMEA and maintenance planSupport and participate in RCM design activities.Master the communication among the diagnostic MMI interfaces, TCMS, the specific on-board subsystem controllers and on-ground systemWrite and review maintenance procedures and plans, train users on CBM.To undertake any other reasonable duties and responsibilities as may be required
Requirements
At least one year experience in railway domain (preferred) or other manufacturing industry such as avionics, automotive or R&DExperience in coding with Python, SQL, and versioning tools (SVN, Git)Familiar with PowerBI and Grafana dashboard developmentAble to interpret electrical drawings, system specification software specification (e.g., UML) and mechanical drawingsBuild, run and monitor production code (e.g., on Kubernetes) using pipelines, reusable components, and schedulingExperience in time-series/forecasting models for anomaly detection, RUL/survival analysis and CBM algorithms.Experience in statistical analysis including quality control, regression models, re-sampling techniques and error/false‐alarm minimization in operational contextsExperience in big data analysis techniques both unsupervised and supervised machine learning and deep learningGood understanding of RCM methodologyAble to write technical specification for software and electronic systemsAn understanding of health and safety requirements of a working environment
Qualifications
Degree in Engineering or Computer science
Desirable Requirements
Experience writing production‐ready Python code and building Grafana dashboards (Preferred)Experience querying large datasets with optimized SQL (Preferred)Experience in maintenance of vehicle railways equipment (Preferred)
Sede Napoli (ibrido 50%)#J-18808-Ljbffr