[What the role is]

[What you will be working on]

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.

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.

[What we are looking for]

• 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.