As a Senior Data Scientist within the Decision Science Home Buying Modelling Team, you will lead the development and management of cutting-edge models that drive decision-making and deliver high-impact outcomes for the Home Buying portfolio. This role combines technical expertise, leadership, and strategic thinking to solve complex business challenges within the credit risk domain for retail banking home loans.
In this role, you will mentor a team of data scientist professionals, collaborate with key stakeholders such as Product/Credit Risk/Finance/Group Treasury across the business, and ensure leverage advanced data science techniques to enhance customer experiences, optimize portfolio performance, and ensure compliance with regulatory standards.

This role supports the Senior Manager in Home Buying Modelling to deliver impactful modelling solutions. You will be responsible for the development and management of key credit risk models within the team, with an objective to foster a team vision that utilises state of the art data science and statistical techniques to outperform the market with regards to credit risk origination and portfolio management. You will be expected to drive higher quality/efficient use of data through continuous process improvements. More specifically this will include:

Leadership and Collaboration

• Lead and mentor junior data scientists, fostering a culture of technical excellence, collaboration, and professional growth.
• Translate complex business challenges into data science problems and actionable solutions.
• Work closely with senior stakeholders across Finance, Portfolio Teams, Product, Pricing, and Risk to deliver data-driven insights and strategies.
• Present technical solutions and insights to senior non-technical stakeholders, ensuring clarity and alignment with business goals.

Model Development and Innovation

• Develop, maintain, and monitor application, behavioural, and operational models across credit risk, pricing, marketing, and operations to optimise portfolio performance.
• Utilize advanced data science techniques and tools (e.g., Python, R) to create industry-leading models.
• Drive continuous improvement in data quality, processes, and model efficiency.

Business Impact

• Deliver timely, high-quality statistical models that address key business challenges and align with regulatory and governance requirements.
• Provide implementable solutions that drive profitable growth, productivity, and customer value.
• Collaborate with the broader Data Science community to maintain a centre of excellence for data-driven decision-making.