Credit Risk Modeler, Customer Experience & Analytics

  • Competitive
  • Kuala Lumpur, Federal Territory, Malaysia
  • CDI, Plein-temps
  • Hong Leong Bank Berhad
  • 17 août 17

Credit Risk Modeler, Customer Experience & Analytics

HLB is embarking on a comprehensive multi-year regional BIG DATA and Analytics transformational journey encompassing products, channels and services across the different markets. We are seeking motivated and skilled professional with solid change management, business process improvement, and strong business acumen with hands on approach to complete assigned tasks within tight deadlines. The candidate must be a team player and result oriented, poses excellent communication and presentation skills, and able to work under tight timeline.

As Analytics Lead of Decision Management Unit, you'll lead a team that's building next generation information and analytics capabilities for HLB, applying the cutting edge in real time banking technologies, using transaction information for tens of millions of customers, and leveraging alternative data sources to secure and enhance the financial wellbeing of people, customers and communities. Your efforts will enable financial inclusion for everyday people and small businesses across the globe making a tangible positive difference in:-

  • Driving the innovation cycle by working with business and risk to identify the next opportunity and develop advanced analytics solutions that push forward our thinking
  • Providing thought leadership to the future of modelling and analytics in financial services, you will lead a team tackling some of the most demanding risk and customer behaviour problems
  • Overseeing/directing the design, development, and evaluation of predictive models/advanced algorithms that lead to practical solutions
  • Motivating and mentoring a team of behavioural economists, data scientists and modellers to grow their skills and careers
  • Optimising risk/return outcomes through creation of decision strategies/campaigns/rules leveraging predictive models
  • Managing relationships with internal clients and vendors
  • Co-leading with business and technology partners negotiations to source data, purchase technologies or partner on fundamental research
  • Investigating the impact of new computing technologies, new sources of data and niche, cutting edge analytical techniques and specialised applications, on the future of banking. Evaluating which ones will enable us to move forward faster and which ones are just a distraction

Qualification / Requirements:-
  • PhD/Post Doc in any field with advanced quantitative focus or Masters degree with high distinction in modelling oriented discipline including but not limited to Statistics, Mathematics, Physics, Chemistry, Biology, Engineering, etc
  • Experience in leading modelling and analytics teams within a global international information-based company or a corporate innovation research lab or a consulting firm. Expertise in small business or consumer risk or marketing, especially scoring and forecasting models, is particularly useful.
  • Demonstrated capability in turning "blackbox" algorithms into attributes and calculations appropriate for risk and pricing and translating analysis findings into solutions in a highly regulated environment
  • Sound knowledge and application in the following:
    • Advanced statistical methods including complex multivariate statistical methods, discrete choice modelling, conjoint based analysis
    • Machine learning including Bayesian methods, neural networks, etc..
    • Excellent knowledge of data mining / predictive modelling
  • Extensive experience meeting regulatory reporting requirements for model usage in banking or another regulated industry, (Customer inquiries, adverse action reason reporting, impact analysis, etc.