Data Scientist

Join a team where you'll have a positive impact on customers' lives, strengthen local communities, and build a rewarding career.

In this role, you will:

• Identify and optimise customer cohorts for home lending opportunities, leveraging a mix of advanced analytics, data science and predictive modelling to drive targeted customer engagement.
• Design, execute and measure experiments to evaluate the effectiveness of customer propositions, using statistical analysis and experimentation frameworks to generate actionable insights and improve outcomes.
• Develop and apply AI-powered solutions, including GenAI and agentic capabilities, to enhance customer communications, improve personalisation and create seamless customer experiences across the lending journey.
• Determine whether a problem is best addressed through machine learning, statistical techniques, rules, an agentic application or a combination of approaches.
• Develop robust experimentation and evaluation frameworks that assess technical performance, reliability, customer relevance and commercial impact.

Bring strong foundations in statistics, mathematics and machine learning, together with demonstrated experience applying data science to complex, commercially meaningful problems. You'll combine technical depth with sound judgement, clearly connecting model and agent design decisions to customer outcomes, operational use and measurable business value. Ideally, you will have:

• Strong practical experience developing, evaluating and implementing machine learning or statistical models using large and complex datasets.
• Experience with supervised learning, predictive modelling, classification, forecasting or related machine learning techniques.
• Experience developing agentic AI, generative AI or large language model applications, including workflow design, evaluation methods and appropriate human oversight.
• The ability to compare machine learning, rules-based and agentic approaches, then select an effective solution based on the problem, available data, risk and expected value.
• Strong Python and SQL capability, with the ability to produce readable, testable and maintainable analytical or application code.
• Experience defining evaluation measures that extend beyond model accuracy to include reliability, customer relevance, adoption and commercial outcomes.
• An understanding of model validation, responsible AI, data governance, fairness and the safe use of customer data.
• Strong communication and influencing skills, including the ability to explain complex technical concepts, challenge assumptions and recommend a clear course of action.