Leading data scientist chapter; Responsible for capability development; build up diverse background data science team; recruit, motivate and coach people.Organizer of Data Science Guild at enterprise level to drive continuous and collaborative learning.Data science road map development in supporting business teams.

Applied SAFe (Scaled Agile); Led cross functional data professionals (including data engineers, BI analysts and data scientists) to solve business problem.Analytical problem framing and created analytics road map for business. Both heuristic and algorithmic based solution.Experienced in delivering various analytical use cases cross marketing, products, channel and operation. e.g. personalized customer targeting; campaign effectiveness reporting with standardised measurement; business process intelligence and diagnose; network optimization and geospatial insights; customer behavior pattern identification in labeling and segmentation.

Ran cadence with business partners to review the impact of model performance on business results. Drove change and recommendation.Developed credit risk model monitoring dashboard for both front end (external and internal marketing strategy change on customer population) and back end (existing customer behaviour tracking and model performance metrics tracking)Provided insights and causal analysis on key risk metrics change. Data quality framework set up and provided sign-off point on reporting data. Responsible for creating single source of truth data by reconciliation and co-creation with different teams. Delivered regular bank risk public disclosureSkills: data quality framework; end-to-end reporting; insights and analysis; coordination and collaboration

End-to-end credit risk models and scorecards development and monitoring for banking products.Basel capital modelling for PD, EAD and LGD. Experienced in risk measurement and calculations for EL, CP, RWA under BASEL and regulatory requirements.Skills: segmentation, data mining, variable construction and selection, bias testing, model development and validation in SAS; Deep understanding in product knowledge and customer behaviour