Employment Type
Application Dates
Opportunity Overview
Graduate Jobs
Competitive Salary
Required Level of Study
Bachelor degree
Areas of Work
Accountancy and Financial Management
IT and Technology
Degrees Accepted
E Engineering, Maths, IT & Computer Sciences
Computer science & IT
Maths, statistics & related

Data Analyst

Job Purpose:

To collect, analyse, and interpret data to support decision-making, improve operations, and enhance efficiency within SMRT.


  • Gather and organize data from various sources, including ticketing systems, onboard sensors, maintenance logs, and customer feedback.

  • Maintain and update databases to ensure data accuracy and completeness.

  • Utilize data analysis tools and techniques to extract valuable insights from the collected data.

  • Perform statistical analysis to identify trends, patterns, and anomalies in railway operations.

  • Develop and maintain key performance indicators (KPIs) for various aspects of railway operations, such as on-time performance, passenger load, and maintenance schedules.

  • Regularly monitor and report on KPIs to relevant stakeholders.

  • Build predictive models to anticipate maintenance needs, passenger demand, and other relevant factors.

  • Use predictive analysis to optimize scheduling and resource allocation.

  • Ensure data security and compliance with relevant regulations and industry standards, especially in handling sensitive information.


  • Degree holder or relevant experience in a relevant field (e.g., data science, statistics, mathematics, computer science).

  • Fresh graduates are welcome to apply

  • Proficiency in data analysis tools and software such as Excel, Python, R, or SQL.

  • Strong analytical and problem-solving skills.

  • Familiarity with data visualization tools like Tableau or Power BI.

  • Knowledge of railway industry operations and terminology is a plus.

  • Good communication skills to convey complex data findings to non-technical stakeholders.

  • Attention to detail and the ability to work independently.