Head of Decision Management SG at CIMB Singapore

, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

0.0

Posted On

14 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analytics, Decision Management, Customer Segmentation, Machine Learning, AI Techniques, Statistical Models, Data Engineering, Data Visualization, SAS, Python, MS SQL, R Programming, Business Problem Solving, Analytical Skills, Communication Skills, Leadership

Industry

Banking

Description

Responsibilities: Overall Define the overall CBGS’ data analytics strategic and focus areas. Working closely with business functions/products and external parties to focus efforts to identify business growth opportunities and drive corresponding solutions to capitalize on the opportunities. This includes (not limited) to analysing and enhancing customer segmentation strategies, event-trigger strategies, channel engagement strategies aimed at acquiring, deepening or retaining customer relationships. Support Consumer Banking’s business performance through analytics driven decision making process across multiple customer segment/product portfolio. Support key business decision making by delivering relevant and value added strategic and tactical analytics and ensure insights are actioned through campaign/marketing and products. Leverage on analytics and data science to drive optimal decision-making across customer lifecycle (from NTB to ETB to good ETB/loyal), customer segmentation, products lines and credit lifecycles. Data Analytics Lifecycle management – Data to Insights, Action, and Feedback Data Engineering and Platform Collaborate with ITD and IT SA for designing, building, and maintaining the infrastructure that supports data storage, processing, and retrieval. Develop data pipelines that move data from source systems to data warehouses, data lakes that enable data extraction and transformation for predictive or prescriptive modeling. Assess the effectiveness and accuracy of new data sources and data gathering techniques and make full use of and expand usage of internal / external data and proprietary / open source analytics tools. Data Analytics, Modelling and Business Decisioning Drive the use of decision rules, event-based triggers, statistical models, machine learning and AI techniques for automation of wide range of business decisions and operations for optimized ROI and revenue per business decision. Lead to develop custom data models and algorithms to apply to data sets via AI/ML. Ensure the development of testing frameworks to assess model quality and accuracy. Deliver consumer insights to business units like products, marketing, customer relationship management and credit operations. Lead to perform business simulations and what-if analysis based on business inputs and market sentiments. Collaboration & People Management Champion projects that acquires, host, process and deploy data flows and models with clear business objectives. Foster and enable a data-driven decision-making culture. Coordinate key initiatives and manage business relationships with key business partners like Risk Management, Finance, IT, Regional counterparties, Credit Bureau, and vendors. Provide guidance to team members as needed on analytic approaches, processes, tools, and problem solving. Supervise the team to manage end-to-end campaign data execution, customer segmentation, CRM, Credit Bureau and MIS solution for the Consumer Banking business and ensuring compliant to the bank’s policy, data management standards and regulations, and accuracy and timeliness in data request deliverables. Requirements: Qualifications Degree in Engineering, Finance, Mathematics, Statistics or other quantitative fields Relevant Work Experience Minimum10 years of relevant experience in customer data analytics and decision science domain Strong analytical skills and good knowledge of the banking industry, especially in consumer business area Past leadership or coaching experience to analytics team(s) Experienced in scoring, propensity modelling, machine learning and optimization techniques with proven results Working knowledge of SAS, Python, MS SQL, R and data visualization tools Competencies/Skills Proficient in SQL, SAS, Python and R Programming Adept at business problem statement and solutioning with strong domain knowledge in the banking industry Strong analytical and communication skills

Responsibilities

Define the overall data analytics strategy for Consumer Banking and support business performance through analytics-driven decision-making. Collaborate with IT to maintain data infrastructure and drive the use of advanced analytics for business decisions.