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Engineering the intelligence layer of LTA's Railway Common Data Platform, you will design and deploy ML solutions that detect anomalies in railway time-series data and provide actionable insights for maintenance and operations. The role blends deep technical work with a focus on delivering tangible value.
You will translate real-world use cases into data problems, build end-to-end models from discovery to monitoring, and collaborate with cross-functional teams to improve rail performance and
SENIOR/ DATA SCIENTIST
The Rail Digitalisation Division is a cross-functional and multi-disciplinary team set up to drive and deliver LTA’s Railway Common Data Platform (CDP), which includes data analytics and artificial intelligence capabilities to support rail performance and operational/maintenance enhancements. You will be responsible for building the "intelligence layer" of the CDP, developing systems that not only detect anomalies in complex railway time-series data but also reason about them to provide clear, actionable outcomes for maintenance and operations. We are seeking a Data Scientist / Senior Data Scientist who excels at converting use cases into a data problem and analyzing data to generate value to support decision making. You should have a proven track record of delivering end-to-end machine learning solutions—from data discovery and feature engineering to model deployment and monitoring. The ideal candidate balances deep technical expertise with a value-driven mindset, ensuring that analytical outputs directly translate to better cost efficiency and improved commuter experience. A degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field is required.
Background knowledge in Computer Engineering, Data Science, Statistics, Computer Science, Engineering, or a related quantitative field is required. At least 2 years of proven relevant experience in data science, preferably with data-heavy industrial or enterprise products. Experience in transportation, IoT, or large-scale condition-monitoring systems with AI agents is advantageous. Those without working experience but has strong interest in quantitative fields are welcome to apply. Successful candidates may be expected to undertake technical assessments or case study presentations as part of the interview process. As part of the shortlisting process for the role, you may be required to complete a medical declaration and / or undergo further assessment.
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