About the role
AI summarisedHead of Decision Management for Consumer Banking at a bank, responsible for defining data analytics strategy, driving business growth through analytics, and leading a team to deliver insights across customer lifecycle. Requires 10+ years in customer analytics and decision science, with expertise in SAS, Python, R, and machine learning.
BusinessFull-timeGeneral
Key Responsibilities
- Define the overall CBGS' data analytics strategic and focus areas.
- Work closely with business functions/products and external parties to identify business growth opportunities and drive corresponding solutions.
- Analyse and enhance 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, customer segmentation, products lines and credit lifecycles.
- 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.
- Drive the use of decision rules, event-based triggers, statistical models, machine learning and AI techniques for automation of business decisions and operations.
- Lead to develop custom data models and algorithms to apply to data sets via AI/ML.
- Deliver consumer insights to business units like products, marketing, customer relationship management and credit operations.
- Champion projects that acquire, host, process and deploy data flows and models with clear business objectives.
Requirements
- Degree in Engineering, Finance, Mathematics, Statistics or other quantitative fields.
- Minimum 10 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.
- 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.