Join us as an Empirical Behavioural Scientist, Behavioural Risk

• Play a key role in applying cutting-edge behavioural science, empirical social science, and data science methods to deliver high-impact audit and research engagements
• Help drive tangible impact by generating robust evidence on how customer and organisational behaviours influence outcomes, decision-making, and risk, answering strategically important questions
• Influence senior decision-makers by applying rigorous empirical methods to critical issues, helping shape the future application of behavioural science within Internal Audit and the bank more broadly

What you'll do

As an Empirical Behavioural Scientist, you'll deliver and, at times, lead behavioural risk audits and research engagements. You'll also design, execute, and interpret empirical research using behavioural science, statistics, causal inference, and generative AI technology, helping to provide insights and assurance on issues that matter to customers, colleagues, and the bank.

In addition, you'll be:

• Designing and delivering empirical research and audit work using behavioural science, quantitative analysis, and causal inference methods
• Translating complex evidence into clear, concise, and compelling insights and recommendations for technical and non-technical stakeholders
• Supporting the adoption of scientific thinking, empirical research methods, and innovative analytical approaches across Internal Audit and the wider bank
• Coaching colleagues and contributing to a collaborative, intellectually curious, and high-performing team culture
• Maintaining audit and research documentation, contributing to risk intelligence activities, and staying at the forefront of developments in behavioural science, data science, and generative AI

The skills you'll need

We're looking for someone with a degree, or equivalent experience, in behavioural economics, economics, psychology, or another relevant empirical social science discipline, as well as experience applying rigorous research methods to real-world problems.

You'll also need:

• Strong experience in designing, conducting, and interpreting empirical research, including experimental, quasi-experimental, or other quantitative approaches
• Expertise in statistics, causal inference, and the analysis of large or complex datasets, with the ability to develop and test hypotheses
• Strong coding capability for research and statistical analysis, such as Python, alongside the ability to draw robust conclusions from multiple data sources
• Excellent communication skills, with the ability to explain complex analytical findings clearly and persuasively to diverse audiences
• A collaborative mindset, enthusiasm for coaching others, and curiosity, as well as adaptability and a desire to learn and innovate
• Experience with large-scale datasets, SQL, code quality practices, behavioural science applications, financial services, audit, or generative AI would be advantageous