[lta-tro] Executive/ Engineer, Innovation & Analytics

[What the role is]

We are seeking a dynamic professional to join our team to transform traffic operations and road assets management through data-driven solutions and innovative technologies. This role combines analytical expertise and ops-tech integration skills to enhance the reliability, performance and sustainability of our road network.

[What you will be working on]

• You will have the opportunity to drive meaningful change through integrating advanced data analytics and geo-spatial insights into operations.

• Collaborate with cross-functional teams to understand their concept of operations, data analytics needs, and translate complex data into user-friendly dashboards, compelling insights and actionable strategies that reshape how we manage our road assets and traffic.

• Manage innovation and data-driven projects which includes application research and product developments.

• Collaborate with internal divisions, external academia and industry partners to explore technologies to transform the way we work. You are required to keep abreast of advancements in smart technologies, big data and other intelligent tools to enhance traffic operations and road asset management practices.

[What we are looking for]

• Tertiary qualification in Engineering, Computer Science, Data Science, Geographic Information Science (GIS), or other related technical fields;

• Strong programming skills, such as Python and SQL

• Experience with GIS tools (such as ArcGIS or QGIS) and data visualisation software (such as Tableau or PowerBI);

• Strong problem-solving ability;

• Organised and meticulous;

• Self-motivated, adaptable, fast learner with a strong sense of responsibility;

• Ability to work independently and collaboratively in a team environment;

• Good writing, communication, analytical and interpersonal skills; and

• Experience in or good knowledge of the following will be an added advantage:

• Traffic engineering

• Data processing including geospatial analysis, statistical analysis and ‘big data’ applications

• Artificial Intelligence and/or Machine Learning models, such as graph neural networks (GNN) or related prediction models

• Best practices in finding insights from data visualization and ability to create interactive and engaging visual representations of data