KEY ACCOUNTABILITIES

Manage, plan and maintain the facilitation of support for data analysis across Eaglestar’s growing global fleet .
Project-manage and deliver on data-related implementations ensuring that deliverables are met within agreed scope and timelines
Manage, develop, and provide Eaglestar’s internal/external stakeholders with various analysis, reports on monthly, quarterly and yearly basis.
Perform ETL on large and complex datasets for AI applications - work closely on performance optimization of large-scale ML/DL model training.
Manage, plan and design relevant Planned Maintenance System reports as requested by Fleet Operations and QAHSSE.
Manage and plan the implementation of Planned Maintenance System data on Eaglestar’s new vessels in collaboration with Group ICT, system vendors and newbuilding site office.
Manage and control system enhancement initiatives as per user feedbacks to enable the full optimization of analysis within ERP system by ship and shore personnel.
Enhance networking and relationship with external peers working in the similar capacity and functions, with the objective of contributing new ideas and improvements to enhance the operational and technical excellence of Eaglestar’s fleet of vessels.
Ensure that the data management team delivers the requirements for all stakeholders as per plan as app
Any additional work as appropriate and delegated by the head for the organizational requirements and growth.

KNOWLEDGE & EXPERIENCE REQUIRED

Professional Qualifications

Degree in Marine Studies/Marine Engineering/ Naval Architect/Mechanical Engineering, Finance, Economics, Computer Science, Data Science, Engineering or equivalent field.

Specialist Knowledge / Skills

General knowledge of global shipping industry and fleet technical management.
Expert working knowledge on SQL and Python/Scala/R/Jason to perform data processing, building data models, conducting data analysis.
Exceptional visualisation skills using Powerbi, Tableau, Qlikview, Qliksense or other relevant visualisation tools.
Well versed in Python programming especially handling large volumes of data both in traditional and distributed environments - pandas, numpy, scikitlearn, pySpark
Well versed with structured (SQL) and unstructured (noSQL) database in traditional and Big data environments (Hive, Spark)
Well versed with concepts like containerization (Dockers, Kubernetes, Openshift), workflow management (AirFlow), streaming data (Kafka or Spark Streaming), CICD pipeline (Jenkins).
Experienced in shell scripting and writing schedulers, Some experience with Cloud deployment (AWS / Azure / GCP) would be a big advantageous.
Strong knowledge of data security best practices

Experience

5 years’ experience in maritime based industries specializing in data analysis and reporting processes.
At least 2-3 years of Software Project Management experience successfully managing both internal stakeholders and external vendors.