Singapore Aero Engine Services Pte Ltd
Design and build analytical tools to provide insight to related engineering KPIs not limited to repair yield, repair callout, repair efficiency, repair effectiveness, component reject mode, etc.
Based on big data, derive predictive solutions to provide guidance to the business including the forecasting of cost, parts replacement / repair, engine workscope, performance, etc.
Automate manual processes, optimize data delivery redesigning infrastructure for greater scalability of extraction, transformation and loading of data.
Identify, design and implement internal engineering business process improvements that will benefit data collection, Extraction, transformation, loading and analysis.
Create and maintain Optimal Data pipeline and architecture to assemble large, complex data sets that meet business requirements.
Use Data Analytics to identify trend and propose potential Life Cycle Cost initiative for win-win benefit.
Work with other engineering teams to assist with data related technical issues and analysis.
Use existing data and engineering knowledge to develop and validate time required to perform a repair.
Lead technical discussion with internal and external stakeholders such as Operations, OEM, customer to agree value engineering issues such as yield, rework, time required to repair etc.
Minimum a Degree in Manufacturing / Mechanical / Computer Science Engineering
Familiar with use of Power BI and Minitab with relevant experiences in programming with VBA, SQL and or C# would be advantageous.
Able to code in Python and is familiar with the use of libraries such as NumPy, Pandas, Scikit-learn and Tensorflow.
Possess good skills in communication, analytics, statistics, data wrangling and business reporting.
Knowledge of component repair processes (e.g. Welding, Plasma, Machining, Coating etc) would be an advantage.
Strong problem-solving and quantitative computational skills
Meticulous and able to work effectively both independently and in a team
Minimally 2 years of experience in a similar capacity in the aviation industry preferred.
Fresh Graduates and engineers (from non-aviation industry) with relevant experiences may be considered.