Data Scientist

Role Overview

Join a growth squad focused on using data, machine learning, and emerging AI capabilities to improve customer experiences within home lending. As a Data Scientist, you’ll develop machine learning and agentic AI solutions that help the business better understand customer needs and support more relevant, informed customer conversations.

What You Will Do

You’ll work with complex datasets to uncover meaningful patterns, develop predictive models, and create intelligent applications that turn data into practical insights. You’ll take ownership across the data science lifecycle, from framing the business problem and evaluating possible approaches through to experimentation, model or agent development, validation, deployment, and monitoring.

Why It Might Be a Fit

We’re interested in hearing from people who bring strong foundations in statistics, mathematics, and machine learning, together with demonstrated experience applying data science to complex, commercially meaningful problems.

Requirements

• Strong foundations in statistics, mathematics, and machine learning
• Demonstrated experience applying data science to complex, commercially meaningful problems
• 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
• Ability to compare machine learning, rules-based, and agentic approaches
• Strong Python and SQL capability
• Experience defining evaluation measures that extend beyond model accuracy to include reliability, customer relevance, adoption, and commercial outcomes
• Understanding of model validation, responsible AI, data governance, fairness, and the safe use of customer data
• Strong communication and influencing skills

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• Paid holidays
• Flexible work arrangements