We operate one of the world's leading and most extensively accepted contactless smartcard payment systems, providing both offline and online payment services. There are over 160,000 acceptance points for Octopus cards in Hong Kong, spanning across the city. We have over 30 million Octopus cards and products in circulation. We handle 15 million transactions a day with transaction value of HK$260 million. Our Vision To become the most preferred payment and lifestyle companion that connects customers and business partners through our best-in-class products and services. Our Mission Making everyday life easier. Our Values Customer Centricity, Simplicity, Inclusiveness & Trustworthiness. Our people are our most important asset. We respect each other, embrace collaboration, innovation and partnership. Come join us and make an impact to the future payment society!

Responsibilities:

• Collaborate with senior management and stakeholders to formulate data strategy with roadmap, advocate data democratization and cultivate data culture in the Company.  
• Lead a team of data professionals to develop AI and Machine Learning solutions to optimize business performance across different areas of the Company. Apply advanced statistical methods and data modeling to analyze complex data sets ,generate actionable analytics/ insights and extend it as an integral component of business growth
• Apply solid experience of digital marketing and loyalty program supported by data modelling to expand payment business and explore new business opportunity 
• Use key tools of analytics and data science to come up with solution and algorithm with measurable impact and appropriate verification plan. Evaluate new capabilities in advancing the analytical power of the Company
• Utilize data visualization tools to communicate findings and insights effectively to both technical and non-technical stakeholders
• Establish and maintain a data governance framework to ensure the integrity, security, and compliance of data across the organization

Requirements:

• University degree in Computer Science, Quantitative or equivalent disciplines. Graduate or advanced degree qualification in related subjects e.g.  Data Science, Statistics, Maths etc
• At least 10 years of proven experience in managing and delivering cloud-based Data or AI/ML applications 
• Solid  experience in leading data team including data scientists or data engineers  to deliver Data or AI/ML applications
• Proven track record of leveraging large amount of data to drive business impact
• Hands-on experience of applying data modelling for digital marketing and loyalty program for business expansion 
• Strong business sense with technical skillset
• Good understanding on the prevalent NLP-related algorithms and models like Transformer, GPT, Bert etc.
• Have hands-on experience with deep learning framework like Tensorflow, PyTorch.
• Familiar with data science libraries like Pandas, Spark, Numpy, Scikit-learn etc.
• Strong programming skills in Python, SQL and SAS.
• Have experience with Azure and Databricks will be an advantage

We offer successful candidate an attractive remuneration package and excellent career prospects. Interested parties please send your resume, present and expected salary, contact details and quoting the reference number by clicking "Apply Now"

Visit our web site: http://www.octopus.com.hk/

The personal data collected will be used for recruitment purposes only. If you are not contacted by us within six weeks, you may consider your application unsuccessful. Personal data with an unsuccessful applicant will be destroyed 12 months after rejection of the application. During this retention period, you have the right to request for correction or destruction of your personal data at any time. Any request for the correction or destruction of personal data should be addressed in writing to our Human Resources & Administration Department.

We are an equal opportunity employer and will ensure that every job applicant and staff has equal employment opportunities and will not be disadvantaged because of their sex, pregnancy, marital status, family status, disability or race.