Manager, Personal Financial Services (Data Scientist)

Requirements

• Minimum 3 years' experience in related field
• Special Skills
• Excellent understanding of and proficiency in SQL and Python. Capable of scripting in SQL and using tools like Tableau. Experience with a Gauss DB Solutions environment and SAS is an asset.
• Modelling experience is a must. eg. Segmentation, propensity, etc .
• Knowledge of banking products is an added advantage.
• Creative thinker and able to identify innovative solutions to current environment
• Strong project management skills, with the ability to lead data science projects from ideation to implementation.
• Strong analytical and problem-solving skills, with the ability to analyze complex datasets and identify insights.
• Strong communication and interpersonal skills, with the ability to effectively communicate findings and recommendations to both technical and non-technical stakeholders.
• Familiarity with Google Cloud Platform (GCP) and its data science services (e.g., Vertex AI, BigQuery, Model Garden)
• Experience with MLOps practices and tools
• About Hong Leong Bank
• Realise your full potential at Hong Leong Bank by applying now.

Benefits

Additional Information

If you are looking to excel and make a difference, take a closer look at us... We are seeking a driven Data Science Manager to lead Hong Leong Bank's analytical transformation through innovative AI/ML frameworks that drives Personal Financial Services (PFS) business sales, revenue and operational efficiency. In this pivotal role, you will provide strategic oversight and technical mentorship to junior data scientists, ensuring all initiatives deliver high-quality, real-world business impact aligned with our AI strategy. Functional (job responsibilities) Initiate and run analytics projects for the Personal Financial Services (PFS) units to drive sales, increase revenue via cross sell and up sell, improve customer retention and engagement, develop, and continuously improve customer segmentation using Advanced Data Analytics, Machine Learning, Artificial Intelligence, etc. Embed the use of data analytics to assist business decision making. Eg. Sales and acquisition strategy, revenue generation through up sell and cross sell, etc. Drive operational efficiency and effectiveness improvement in the team using innovation and technology. Eg. Stream lining processes, automating manual processes, campaign tracking, etc. Managing data-driven projects from conception to completion, ensuring that they are completed on time, within budgets and meet the desired goals and objectives. Working closely with stakeholders and decision-makers to understand the business requirements and develop data-driven solutions that address those needs. Analyzing large and complex datasets, applying statistical and machine learning methods to extract meaningful insights and develop predictive models. Creating clear and compelling data visualizations and reports to communicate findings and recommendations to the stakeholders and decision-makers. Possessing excellent communication and interpersonal skills, with the ability to effectively communicate findings and recommendations to both technical and non-technical stakeholders. Staying up-to-date with the latest data science tools and techniques, and continuously learning and improve skills to stay at the forefront of the field. Play an active role in the overall bank and department AI strategy. Managerial (team/group responsibilities) Conduct code review and Provide mentorship to the junior data scientist to ensure that they have the skills and knowledge necessary to deliver high-quality solutions. Organizational (organizational responsibilities) To ensure alignment to the Division and Bank's strategic intent and goals for the financial year. Education/Qualification Degree in Data Science, Actuarial Studies, Banking/Finance, Business, Marketing, Mathematics/Statistics, Market Research or related disciplines

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