Assistant Manager/Manager - Credit Risk Strategy - Lifecycle Analytics & SAS

Looking for good experience in Credit Lifecycle - Credit Authorization, Credit Underwriting, Origination, Credit Acquisition, Collection Strategy, Customer Management etc with good experience of SAS and Analytics.

High level Role Description

- Conduct portfolio analytics and deep dives as required by country/regional/Group Retail Credit. Develop credit strategies across the customer lifecycle of Origination, Portfolio Mgmt and Collections.

- Create insights for Retail Risk by studying portfolio trends, performing necessary analytics such as segmentation, profiling, cut-off setting, stress testing, sensitivity analyses

- Timely identification of shifts in portfolio risk profile and re-aligning risk-measurement tools for effectiveness and continuously enhance data-driven credit decisions

- Provide analytical support to various Risk Reviews, perform adhoc analytical requests to support policy changes

- Participate in selective strategic initiatives to build and enhance Group's in-house analytics capabilities

Competency expected in role

- Strong logical reasoning ability. Ability to perform various industry standard complex statistical analysis in relation to credit risk problems

- Ability to work with data organized across platforms and formats (RDBMS tables, SAS datamarts, Excel spreadsheets, text files)

- Ability to bring out meaningful and actionable insights from unstructured data e.g. transaction data

- Ability to blend in existing BAU analytical projects and processes in a seamless manner

- Maintaining the desired quality of analytics within stipulated timeframe

- Ability to work with multiple departments and stakeholders within the Bank to achieve end results

Eligibility criteria

- Advanced degree (preferably Masters) in a Quantitative Discipline (e.g. Math, Stat, Eco, Engineering, Finance, MBA)

- 2-5 years desired relevant work experience

- Proficiency in SAS is a MUST with proven experience of working with large, complex data

- Proficiency in Microsoft Excel and PowerPoint is a MUST for the purpose of analysis, presentation and visualization. General familiarity with all Microsoft Office applications.

- Proficiency in SAS Enterprise Miner is preferred

- Knowledge of other analytical tools such as R, Python, Tableau etc will be a PLUS

- Sound knowledge of Financial Services products, in particular Retail Banking, is a MUST including a good understanding of product economics

- Sound knowledge of Credit Risk is desired with ability to perform related data analysis

- Good written and verbal communication skills