Data Science Analyst

About Fleet Management

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 Fleet, 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 Fleet'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.

Key Roles and Responsibilities

As a Data Science Analyst, your typical day will include:

Charting the Course: Development of the NOVA Analytics Platform

• 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

Signaling Insights: Stakeholder Management & Communication

• Act as a lighthouse for our company - provide clear and compelling insights into the business through dashboards and ad-hoc analysis
• Translate complex data findings into clear reports and presentations for senior leadership to guide strategic decisions
• Partner with maritime subject matter experts to translate their deep domain knowledge into powerful, data-driven solutions
• Create clear and concise documentation for all analytical solutions to ensure they are understandable and maintainable

Being an Anchor for the Crew:

Teamwork

• Collaborate with the IT team to build high-quality, robust, and scalable solutions that balance technical rigour with real-world usability
• Promote data literacy across Fleet Management and drive adoption of analytical solutions by clearly explaining the impact of your work
• Champion data governance and best practices to ensure the quality and integrity of our data assets

Relationship (mostly Internal and or External) and Nature of Communication:

INTERNAL:

• Development Teams (based in HK & India); Ops & Support (based in HK & India); Stakeholders – Director-level and below

EXTERNAL:

• Interaction with vendors/third parties

Job Experience, Functional Knowledge and Qualifications

Essential :

• 3+ years’ experience in a Data Analytics or Data Scientist role
• Hands-on experience across the entire life cycle of an analytics solution
• Database technologies (e.g. SQL, NoSQL, Graph Databases)
• Written queries to extract data and perform complex transformations and joins so that it can be used for modelling or dashboard development

Data Visualisation Tools (e.g. Tableau, Power BI):

• Single-handedly developed, launched, and maintained multiple dashboards; can explain the purpose of the dashboards and visual choices chosen to generate insights

Data Science and Model Development (e.g. Python, R):

• Built machine learning models from scratch (data preparation, feature engineering, model training/validation, model deployment). Familiar with modern ML packages (e.g. Scikit-learn, Pytorch)

Programming Development (e.g. Git):

• Have a strong emphasis on code versioning, tracking and proper development practices (documentation and commenting)
• Experience with and comfortable speaking with senior stakeholders (Director-level) to gather requirements for analytical solutions, leading user testing, and presenting solution to company leadership
• Independently delivered end-to-end projects and insights that improved business processes, driven the adoption of new methods, or launched a new solution, yielding quantifiable benefits
• Excellent communication and presentation skills in English

Desirable

• 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

Competencies

Analysis & Problem Solving (Level 2):

Uses critical thinking to address problems. Able to perform root cause analysis on complex problems to identify underlying trends and put forward well-thought out solutions to address the causes

Listening & Communicating (Level 2):

Focuses on the individual they are communicating with. Writes and expresses thoughts clearly adjusting as necessary to the audience. Asks questions to clarify

Collaboration, Inclusion & Teamwork (Level 1):

A good team player that is personable, friendly, polite and takes the time to know people. Collaborates with onshore and offshore colleagues well

Customer Focus (Level 2):

Understands the needs of the customer clarifying requirements and expectations. Adapts as necessary to changing requirements and is responsive, helpful with all requests. Sets high quality for service delivery

Planning & Organising (Level 2) :

Uses the supplied tools for structured project planning for optimal time use. Balances competing priorities. Promptly Updates people when plans change and keeps them apprised of progress. Adjusts own plans based on FML strategies and plans

Initiative (Level 2) :

Challenges existing ways of doing things. Looking for continuous improvement without being asked. Identifies ways to improve efficiency and effectiveness in own work and others in the team

Accountability (Level 1) :

Completes routine work independently. Asks for guidance when needed from manager highlighting when errors made. Demonstrates integrity and ethical behaviour at all times