We are currently seeking a high calibre professional to join our team as a Manager – Client Intelligence (Client & Banking Analytics, CIB)
About the Team
The Client & Banking Analytics (CBA) team within CIB transforms data into strategic analytics that drive insight, innovation, and commercial performance across the banking group.
As the business owner of Omnia and CME, CBA helps simplify analytics, enhance business intelligence, and improve client and shareholder outcomes.
We deliver data-driven insights to optimize investment across clients, products, channels, and resources, and to enhance pricing.
This is supported by disciplined governance, consistent methodology, and fact-based analysis.
The Role
As a Manager within the Client Intelligence pillar, you’ll help deliver advanced analytics that commercialize the banking group’s internal client data and integrate external datasets to generate actionable insights.
You’ll own defined analytics workstreams end-to-end (from problem framing to delivery), partnering closely with stakeholders to identify growth opportunities, define high-potential clients, and optimize customer value to guide investment decisions across clients, products, and channels.
Where appropriate, you’ll use approved AI tools, including emerging agentic workflows and AI-driven analytics, to accelerate delivery, with appropriate validation and governance.
In this role you will:
Analytics Delivery: Build, test, and deploy analytical models for client profiling, segmentation, wallet sizing, customer value measurement, and growth use cases.
Use approved AI tools, including agentic workflows, to support analysis and automation where relevant.
Insight Generation & Storytelling: Translate analysis into clear recommendations, commercial implications, and practical next steps for frontline and CIB leadership.
Stakeholder Partnership: Work with coverage, product, and servicing teams to understand needs, refine requirements, and support adoption ...
經驗要求：Entry level
連接業內人士以了解更多資訊（團隊情況、面試重點、申請建議）。
要求
Data & Quality Management: Partner with data engineering/technology to access data, improve data quality, document assumptions, and follow governance standards.
Operational Excellence: Maintain robust model documentation, performance monitoring, and repeatable processes; contribute to reusable code and standard methodologies.
Collaboration & Coaching: Support junior colleagues through peer review, knowledge sharing, and best-practice guidance (without necessarily being a formal people manager).
Bachelor’s degree required; Master's degree holder with solid experience in Data Science area is prefered OR PhD's Degree holder with strong interest to develop their career in banking industry will be considered.
Solid Experience in analytics/data science, ideally within financial services or a commercial analytics environment.
Working knowledge of Python (preferred), SQL; experience with modelling techniques (predictive, statistical, ML). Familiarity with big data and/or cloud environments (e.g., Spark/Hadoop; AWS/Azure/GCP) and visualization tools (Power BI/Tableau).
Experience with disciplined coding practices and have a systems mindset
Familiarity with AI-assisted analytics and a practical approach to when to use it and how to validate outputs.
Working knowledge of CIB client segments and commercial drivers; experience in at least some of: client segmentation, wallet sizing, client profiling, peer benchmarking, pipeline/sales analytics.
Able to explain methods and results to non-technical audiences; comfortable presenting insights to stakeholders and iterating based on feedback.
Comfortable operating in a global matrix; organized, delivery-focused, and able to manage multiple priorities.
