[Lta-Raom] Data Scientist / Data Analytics Engineer (Pam&M)

[What the role is]

[LTA-RAOM] DATA SCIENTIST / DATA ANALYTICS ENGINEER (PREDICTIVE ASSET MGMT. & MAINTENANCE)

[What you will be working on]

You will be part of the asset management team, to develop predictive algorithms and prognostics for decision support in areas of predictive maintenance of railway and digital asset management. You will perform some of the following roles: machine learning, mathematical/statistical analysis, coding, data ingestion/engineering, and system engineering to meet asset management and maintenance outcomes over lifecycle of the assets.
You will work closely with teams from different disciplines within LTA, rail operators, system manufacturers on the data and interfaces of rail assets, as well as set out/explain rail asset management business use cases using data. You are also required to review technical submissions and participate in the testing and commissioning of the predictive/analytical decision support systems.
For senior positions, you will be expected to provide technical leadership to the team in matters of statistics, data science, MLOps and data engineering. Leading and mentoring the junior data scientists / analysts in the team will be one of your important contributions.


[What we are looking for]

• Tertiary qualification in Electrical, Electronics Engineering, Computer Science, Mechanical, Industrial Engineering, Sustainable Infrastructure Engineering or equivalent
• Strong writing, presentation, coding, communication and interpersonal skills
• Team player with critical and logical thinking capability and must be able to work independently
• Experience in (a) IT application, data analytics/machine learning, OR (b) System Engineering or Railway Engineering using data will be an advantage
• Those with relevant years of experience will be considered for senior positions. For senior positions, the following are considered :
- Solid understanding of statistical analysis and predictive modelling / machine learning
- Knowledge of data management, data engineering and data visualization techniques
- Experience with implementing MLOps in an enterprise IT system
- Ability to lead and mentor junior data scientists / analysts