About this role
Salary: £41,500 - 69,500 per year
Requirements: We are looking for an engineering degree, preferably in Electrical or Electronics Engineering.We prefer experience in the railway domain, or in another manufacturing industry such as avionics, automotive, or R&D.We require strong coding experience in Python, SQL, and preferably PySpark, as well as version control tools such as SVN and Git.We are looking for familiarity with PowerBI dashboard development.We need the ability to interpret electrical drawings, system and software specifications such as UML, and mechanical drawings.We value experience in prediction and condition-based maintenance algorithms.We look for experience in statistical analysis, including quality control, multiple linear regression, logistic regression, discriminant analysis, and re-sampling techniques.We value experience in big data analysis techniques, including both unsupervised and supervised machine learning.We are particularly interested in candidates with a background in Electronics Engineering, Software Engineering, Computer Science, Data Science, or a related discipline.Strong Python coding skills and an interest in data analytics, machine learning, or predictive technologies are essential. Responsibilities: We support initiatives that improve service quality and equipment reliability by developing tools, systems, and analytical insights that optimise maintenance processes.We work alongside experienced engineers to gain exposure to Reliability Centred Maintenance and Condition Based Maintenance methodologies, as well as data science techniques applied to operational challenges.We help connect field operations with the maintenance organisation to minimise downtime, reduce failure rates, and maximise fleet availability.We review and design main train subsystems with a focus on maintainability, availability, reliability, and condition-based maintenance rule application.We develop prognostic algorithms based on logic, signals, events, operational information, and maintenance timing requirements.We implement prognostic algorithms using proprietary technologies and coding languages such as PySpark and Python, as well as PowerBI.We analyse diagnostics and maintenance data.We monitor prognostic system performance and perform statistical analysis on collected data to identify critical trends and conditions.We support prognostic algorithm verification and validation, including simulations with a TCMS simulator and historical diagnostic data, and analysis of maintenance reports and field failures. Technologies: Big DataGitSupportMachine LearningPythonPySparkSQLSVNUML More:
We are Hitachi Rail UK Limited, based at our London HQ in London Ludgate, and we offer a full-time junior engineering opportunity on a hybrid working basis for a recent graduate or early-career engineer. This role gives exposure to condition monitoring, reliability engineering, and data analytics within the rail industry. We operate globally and focus on digital transformation, technology, sustainability, and innovation. We offer a competitive salary, 25 days holiday, a pension scheme with contributions up to 9%, private medical insurance, personal accident insurance, group income protection, group life insurance, an employee assistance programme, and additional flexible benefits to suit individual needs and lifestyles. We are an equal opportunity employer and welcome differences in background, age, gender, sexuality, family status, disability, race, nationality, ethnicity, religion, and world view.
last updated 36 week of 2026