Data Scientist

About Company:

Our 30-year journey rides on the passion of over 27,000 seafarers and 1,000 onshore professionals. Today, we are one of the largest independent third-party ship management companies managing over 650+ diverse types of vessels.

Headquartered in Hong Kong SAR, China, we operate on a global scale having 27 offices in 12 countries. Our client base spans over 100 world-class ship owners, including Fortune 500 companies from China, Greece, India, Japan, Korea, Netherlands, Norway, Turkey and the USA, among others.

In a shore career at Company, you will be working with a team of a highly passionate, self-driven and committed group of people. We aim to be a place where you can achieve your full potential, regardless of your background. We are looking for individuals who are ambitious about making a strong contribution to Company's short and long-term sustainable growth – whether you are dealing directly with clients or working in a role supporting the business, such as technology, legal or communications.

An Ideal Candidate:

• Bachelor's or master's degree in mathematics, Statistics, Computer Science, or a related quantitative field
• Experience setting up and managing cloud infrastructure for analytics purposes (e.g., AWS Sagemaker, EC2, Tableau Server)
• Experience in Generative AI model hands-on usage, model tuning, and configuration (e.g., Vertex AI, LangChain, Hugging Face)
• Exposure to Big Data technologies (e.g. Spark, Hive, Presto)
• Certificates in Tableau or native-cloud platforms such as AWS, Azure, or Google Cloud

Key Competencies:

• Manage analytics projects from concept to project planning, delivery, and completion, adhering to the Analytics roadmap
• Source, cleanse, and transform raw data from our big data systems to build a solid foundation for modeling and dashboard development
• Perform exploratory data analysis to uncover hidden patterns and valuable opportunities within our datasets
• Build, validate, and deploy robust machine learning models and implement them into operational processes
• Design, build, and test user-friendly dashboards and analytics tools that are actively leveraged by end-users
• Continuously monitor model performance and dashboard usage metrics to make continuous improvements to existing solutions