The Rail Digitalisation Division is a cross-functional andmulti-disciplinary team set up to drive and deliver LTA’s Railway CommonData Platform (CDP), which includes data analytics and artificialintelligence capabilities to support rail performance andoperational/maintenance enhancements. You will be responsible for building the"intelligence layer" of the CDP, developing systems that not onlydetect anomalies in complex railway time-series data but also reason about themto provide clear, actionable outcomes for maintenance and operations.

We are seeking a Senior Data Scientist who excels at convertinguse cases into a data problem and analyzing data to generate value to supportdecision making. You should have a proven track record of deliveringend-to-end machine learning solutions—from data discovery and featureengineering to model deployment and monitoring. The ideal candidate balancesdeep technical expertise with a value-driven mindset, ensuring that analyticaloutputs directly translate to better cost efficiency and improved commuter experience.A degree in Data Science, Statistics, Computer Science, Engineering, or arelated quantitative field is required.

Technical Skills

• Modeling & Time-Series Analysis: Expert proficiency in Python and SQL. Deep experience in time-series forecasting and anomaly detection (e.g., Z-score, growth rate analysis, and statistical thresholds).
• Data Engineering Synergy: Competence with modern data stacks (e.g., Snowflake, Databricks) and real-time data ingestion via APIs to build scalable, production-ready pipelines.
• MLOps & Automation: Experience in managing the full ML lifecycle, focusing on "operational AI" that triggers automated workflows or maintenance alerts.
• Visualization & UI Collaboration: Ability to translate complex model outputs into requirements for UI/UX designers to create intuitive, data-rich enterprise dashboards.
• Decision Intelligence: Proven ability to build autonomous systems that go beyond simple detection, including experience with AI agents that combine statistical triggers with LLM-based reasoning to automatically categorise, prioritise, and/or escalate operational issues.

Key Attributes

• Analytical Problem Solver: Strong ability to take vague operational "pain points" and structure them into rigorous analytical frameworks that drive ROI.
• Stakeholder Management: Exceptional communication skills to explain algorithmic logic and "uncertainty" to non-technical stakeholders.
• Proactive Learner: A self-starter who stays updated on the latest in Agentic AI and can independently drive design initiatives end-to-end.
• Collaborative: High comfort level working in a "squad" format alongside UI/UX designers, Product Managers, and Railway Engineers.

Requirements

• Background knowledge in Computer Engineering, Data Science, Statistics, Computer Science, Engineering, Business and Commerce or a related quantitative field is required.
• At least 5 years of 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.
• 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 furtherassessment.