Avp, Credit Risk Data Scientist, Credit Risk Modelling

**WHO WE ARE**:
As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future.

We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.

Your Opportunity Starts Here.

**Why Join**:
As a Credit Risk Data Scientist, you will be part of a team that drives the development of advanced analytics and machine learning models to assess and manage credit risk. You will have the opportunity to work with large datasets, develop predictive models, and influence business decisions. Join us and contribute to the bank's risk management capabilities, while building a rewarding career in a dynamic and supportive team.

**How you succeed**:
To succeed in this role, you will need to develop and implement advanced analytics and machine learning models to assess credit risk. This involves collating and analyzing large datasets, identifying patterns and trends, and developing predictive models that can inform business decisions. You will also need to work closely with stakeholders to understand their needs and develop solutions that meet their requirements.

**What you do**:

- Develop, implement, and maintain machine learning credit risk models supporting the Consumer, Small Business and Wholesale segments of the Group.
- Monitor, back-test and report performance of the models to ensure adherence to performance standards and early detection of weaknesses.
- Develop and maintain user requirements, parameters and configurations of systems housing the models.
- Develop in-depth expertise in credit risk modelling methodologies.
- Work closely with independent model validators to ensure compliance to model governance framework and timely closure of validation findings.
- Engage with auditors and regulators to ensure compliance with relevant requirements.
- Engage with various stakeholders to develop analytical solutions using model outputs in credit decisioning, business strategies, allowance, and capital assessment.

**Who you work with**:
**Group Risk Management**

Group Risk Management works independently to protect, build, and drive our businesses. The team supports good decision-making with strong risk analysis and a crucial, comprehensive role in sharpening our competitive edge. Optimising risk-adjusted returns, it's about seeking and adopting best-in-class practices, protecting the group from unforeseen losses, keeping risk within appetite, and embracing change and managing growth in one of the world's strongest banks.

**About the Team**

CRM is a high-profile, multi-disciplinary risk analytics team that covers credit risk models at OCBC Group. The key functions CRM performs include developing, implementing and managing various types of credit risk models, such as Credit risk Scorecards, Internal Rating models, IFRS 9 based Expected Credit Loss models, Credit Stress Testing models, Economic Capital models and Machine Learning models that support Group’s credit risk measurement. These models are embedded in the credit underwriting, customer selection, limit setting, early warning and problem recognition, as well as assessment of capital and provision adequacy.

**Who you are**:

- Degree in a Quantitative discipline, such as Data Science, Statistics, Mathematics or Computer Science.
- At least 5-7 years of relevant experience in a related area.
- Working experience in credit analysis/modelling or credit risk management of Consumer, Small Business and/or Wholesale portfolios.
- Proficiency in common machine learning tools and frameworks (Scikit-Learn / Tensorflow / PyTorch).
- Experience with big data technologies such as Hadoop, Hive and Spark.
- Knowledge in ML-Ops tools and Git.
- Analytical and independent thinker with strong written and verbal communication skills.
- Ability to interact and communicate effectively with senior management.
- Willing to take on new challenges and work in a fast-paced environment.

**What we offer**:
Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.