Senior Manager Data Science – Fraud Analytics

• You are passionate about solving complex problems using Data Science and analytics

• We’re one of the largest and most advanced Data Science practices in the country

• Together we can build impactful data science models that help protect our customers and prevent financial crime

Do work that matters

Business Banking manages relationships with small-to-medium enterprise customers, mid-market corporate customers, and regional and agribusiness clients, delivering a wide range of financial services and solutions.

Within this, Business Lending is responsible for core lending products including working capital, business loans, asset finance, corporate finance, and property finance, as well as Line 1 risk and controls across these products.

You will sit within a team focused on Balance Sheet Management, supporting sustainable and profitable growth through portfolio optimisation, pricing, data governance, and application fraud prevention.

Our team plays a critical role in improving application fraud detection and credit assurance, working closely with bankers, risk, operations, and analytics teams to drive better decision-making and outcomes.

We are on a journey to uplift our analytics capability, moving towards more sophisticated, scalable and impactful data science solutions across fraud and financial crime.

See yourself in our team

• As a Senior Manager, Data Science – Fraud Analytics within Business Banking, you will play a key role in designing and delivering advanced data science models to detect and prevent application fraud.

• This is a hands-on leadership role, focused on building and optimising models that identify high-risk behaviour, improve case prioritisation, and strengthen fraud detection capabilities across Business Banking.

• You will work closely with stakeholders across Business Lending, and Business Bank, financial crime, and retail banking teams to translate complex data insights into practical, business-ready solutions that enhance investigation outcomes and protect customers.

• This is an opportunity to contribute to the evolution of fraud analytics capability, leveraging modern tools and data science approaches to combat increasingly sophisticated fraud threats across a large and diverse customer base.

• In this senior role, you will also build strong stakeholder relationships, guide analytical thinking, and help shape the future direction of fraud prevention through modelling across the organisation.

We’re interested in hearing from people who:

• Have strong hands-on Data Science experience, particularly in building and optimising predictive models

• Are highly analytical with strong attention to detail and the ability to identify patterns in complex datasets

• Can translate technical outputs into clear business insights for non-technical stakeholders

• Have experience working across cross-functional teams, including operations, risk, and business stakeholders

• Are problem solvers who can improve model performance, optimise rules, and drive better decision-making

• Have exposure to fraud, financial crime, credit risk, or related domains

• Bring strong communication and stakeholder management skills

• Can navigate ambiguity and contribute to evolving analytical capabilities

Technical Skills:

We use a broad range of data science and analytics tools. We don’t expect you to know them all, but experience in several of the below will set you up for success:

• Strong programming skills in Python (preferred)

• Experience in statistical modelling, machine learning, and optimisation techniques

• Ability to work with large datasets and build scalable analytical solutions

• Experience in data visualisation and communicating insights effectively

• Understanding of risk, fraud, or credit decisioning frameworks

Note: This role is focused on core modelling and analytics capability uplift. While exposure to AI is valuable, agent-based or advanced Generative AI systems are not a current focus.