Manager, Data Science (Risk & Compliance) | 人才服务办公室

职位描述

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!

Job Responsibilities:

• Responsible for building analytical and scientific solutions to help solving complex and novel problems in risk management with providing timely, accurate and actionable insights
• Conduct risk & complianceanalysis via state-of-art Machine Learning (ML) algorithms, data mining or statistical analysis to forecast probabilities of suspicious behaviour
• Establish robust data model from relevant data collection and preprocessing for analysis, feature selection and engineering, model development, validation and testing to achieve business goal
• Devise algorithms/ machine learning models in cloud data platform to mine big data; perform risk analysis to identify opportunities/ threats
• Support the implementation of different data science applications in cloud platform
• Implement analytical models into production by collaborating with software developers and machine learning engineers
• Utilize data visualizations to present findings and insights that can create business impact
• Clean and validate data for uniformity and accuracy. Explore innovative ways for data integration to enforce good governance on data management and regulatory compliance

Requirements:

• Postgraduate degree in Statistics, Computer Science, Data Science or related disciplines
• Around 6 years of solid experience in data analytics (risk & compliance discipline) and/or related industries with at least 5 years in data science/ cloud platform
• Solid experience of key machine learning and deep learning framework, e.g. Tensor flow, Caffe, CNTK…etc.
• Solid experience in key machine learning and big data cloud platform, e.g. Microsoft Azure ML Services & Data Warehouse, AWS SageMaker & Redshift, Google ML and BigQuery, etc.
• Experience in common data science languages/toolkits, such as Python, SQL, R, Scala, Apache Spark, Keras, etc., to manipulate data and draw insights from large data sets is desirable
• Experience in data architectures and in data visualization BI tools, such as Tableau, PowerBI, Cognos, etc.
• Team player with passion, positive attitude and with good business acumen

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.

Octopus is an equal opportunity employer and all employment decisions and Human Resources policies are administered; especially those relating to recruitment & selection, compensation & benefits, promotion & transfer, training & development and termination & redundancy; without discrimination on the basis of age, race, colour, religion, sex, national origin, marital status, pregnancy, physical and mental disability and family status but on genuine occupational qualification, job performance, employees’ ability and internal/ external relativities.