Vp, Data Scientist, Risk Management Group Data Chapter, Group Transformation

**Business Function**: The Risk Management Group (RMG) Data Chapter plays a crucial role in ensuring the integrity and quality of data used across RMG's risk management functions. We are responsible for data governance, analysis, and reporting, supporting critical decision-making and regulatory compliance. We collaborate closely with various teams to deliver accurate and timely data insights.Responsibility: - Lead the design, development, testing, and operationalization of credit models, rules, and algorithms to enhance the bank’s Eco-System Lending (ESL) capabilities
- Manage the Advanced Modelling Analytics team, providing guidance, mentorship, and support to drive the team’s success and deliver high-quality data scientific deliveries
- Oversee the end-to-end development of credit risk models (e.g., underwriting, propensity, income estimation) for CBG and SME portfolio, ensuring alignment with industry best practices
- Collaborate with cross-functional teams (data scientist, credit risk, fraud detection, business unit, and Middle Office Technology team) to collect, analyse, and interpret complex datasets for effective model development
- Manage the full model lifecycle, including development, back-testing, validation, calibration, and performance monitoring
- Ensure strict compliance with internal risk management policies and regulatory requirements
- Present model development findings and risk assessments to senior leadership, model end-users, and internal validation / audit teams
- Stay informed of the latest advancements in credit risk modelling, machine learning, and advanced quantitative techniques
- Mentor and guide junior team members, fostering a culture of continuous learning and innovation
- Drive automation and process improvements in the model development lifecycle
- Translate complex business challenges into actionable analytics requirements
- Lead the development of AIML models to support the bank’s Analytic-Based Lending (ABL) Strategy, ensuring alignment with business drivers
- Oversee the measurement, development, and execution of initiatives and workstreams
- Build and maintain strong stakeholder relationships, demonstrating the ability to communicate complex analytics insights effectively to deverse audiences
- Foster collaboration between business, technology, and data teams to integrate advanced analytics seamlessly into decision-making processes
- Lead overall reporting and updates to executive forums and key stakeholders Requirements: - Minimum of 10 years of experience in related areas, with a strong track record in credit risk model development and implementation (e.g., Application, Behaviour, Collection, Propensity models)
- Hands-on experience with Eco-System Lending business related models is a must
- Hands-on experience of developing credit risk models and fraud analytics solutions, with sound understanding of credit underwriting process
- Outstanding AI/ML modelling and programming expertise, with proficiency in tools such as Python, PySpark, etc. In-depth knowledge of statistical analysis, econometrics, and machine learning techniques
- Proven ability to work both independently and collaboratively within a team environment
- Exceptional stakeholder management skills, with the ability to convey technical concepts to non-technical audiences and align mutual priorities
- Strong written and verbal communication skills, coupled with the ability to manage complex projects effectively
- Demonstrated leadership in fostering collaboration across business, risk, and technology teams to drive impactful outcomes.