RESPONSIBILITIES

• Monetize data + analytics in support of sales, marketing, product and portfolio managers in the following areas:
  – Prospecting and improving new customer acquisition – segmentation, market/wallet sizing, product proposition, pricing, leads generation + scoring, etc.
  – Growing existing customer franchise and balances – cross-selling, retention, next best offer + conversation, personalized customer engagement (online + offline).
  – Improving digital (mobile app and internet banking) adoption and customer interaction via personalized, omni-channel engagement.
  Candidate is expected to build predictive models/analytics using:
  – A suite of statistical / data science techniques (regression, gradient boosted trees, network analytics, neural networks, NLP, audio/image processing, etc) that is best fit for purpose / use.
  – Both structured and unstructured data (test, audio, image, streams, etc) that can be found within the bank and external partners, vendors or in the internet in general (social media, web-crawled data, etc).
• Work with BB’s ecosystem / partnership team to increase monetization of partner / platform data (eg, e-commerce, payments, ERP solutions, etc), and actively source for new data sources / revenue streams.
• Manage regular marketing campaign operations, including regular reviews and feedback to improve conversion rate / campaign / model effectiveness.
• Work with the Group BBMA team to develop, enhance and manage credit risk models, including: application and behaviour scorecards / rating systems, Basel 2 capital models, IFRS 9 loss provisioning model, and early warning systems.
• Generate regular credit portfolio quality reports and run the monthly portfolio quality reviews with country and Group stakeholders. Conduct ad-hoc / deep dive analyses to identify risk hot-spots and work with the Credit team to address current or emerging issues. Support analytics for product program renewals, including proposing test-and-learn programs to expand / optimize credit policies, approval rates and potential target segments.

REQUIREMENTS

• Over 7 years of experience in retail / SME credit risk and/or marketing analytics roles within a bank, fintech, or consulting environment.
• Undergraduate degree in a quantitative programme, such as Decision Science, Statistics, etc. MBA / post graduate degree is desirable.
• Very strong data/decision science, programming and technology skills:
  – At the minimum, very proficient in SAS for data management and modeling.
  – Advantageous to have proficiency in Python or R for data science and Hadoop ecosystem for data management – uses Cloudera Apache Hadoop big data platform.
  – Adobe Marketing platform (Adobe Analytics, Campaign, etc) for online and offline marketing campaign management and insights.
• Analytical mind with sound business insight, excellent communicator (verbal and written), highly meticulous, and self-motivated.
• Maturity that will enable the candidate to be a credible counterpart to business managers and senior management, and the ability to develop on-going ‘trusted advisor’ relationships based on the ability to understand, analyse, discuss and address key business challenges raised.