Senior Audit Manager, Behavioural Risk & Applied Empirical Science
Join us as a Senior Audit Manager in Behavioural Risk
- This varied role will see you shaping the strategy of our Behavioural Risk team, focussing on driving the adoption of empirical scientific research methods within the team and across Internal Audit
- As well as recruiting, developing, and leading a team of specialists, you’ll build internal and external partnerships, developing your leadership skills while helping colleagues pursue rewarding careers
- You’ll be responsible for shaping and delivering high profile evidence-based and data-led pieces of insight, providing assurance to senior executives on our assets and sustainability
- We’ll look to you to build your understanding of internal audit methods and develop further our behavioural risk audit capability, tooling, partnerships, and practices
What you'll do
As a Senior Audit Manager, you’ll collaborate with audit experts to understand critical business assurance and sustainability questions. You’ll work closely with a diverse group of talented and accomplished behavioural and data scientists, identifying opportunities for innovation while gathering resources and owning implementation.
You’ll also:
- Provide oversight for colleagues designing feasible and impactful research approaches that drive positive change in customer, colleague, and stakeholder outcomes through continuous behavioural risk assessment and monitoring
- Develop and manage effective stakeholder relationships and support colleagues leading individual pieces of work that involve executing and interpreting insights
- Stay on top of, and drive experimentation with the latest applied empirical science and generative AI methods and applications, as well as analysis and workflow management technology
- Stay at the forefront of behavioural science insight, sharing knowledge proactively
The skills you'll need
We’re looking for someone with extensive relevant technical and research leadership experience within a business setting. You’ll hold an academic degree in a social science discipline, with a strong quantitative analysis element, or you’ll have a proven equivalent track record.
You’ll have experience in empirical social science design and execution, covering statistics, causal inference methods, and data science. Knowledge of large-scale business data handling such as databases and SQL would be beneficial, as would an understanding of retail banking, financial markets, generative AI, code development, and quality assurance practices such as Git, GitLab, and GitHub.
In addition to this, we’re looking for:
- Enterprise level coding experience including object-oriented programming, ideally using Python
- Experience in drawing conclusions from different primary and secondary data sources
- Clear, concise, and compelling communication skills to inspire others, maintain momentum, and ensure work completion
- Experience role-modelling, supporting, and supervising through coaching, feedback, and development
- The entrepreneurial skills, resilience, drive, and enthusiasm to develop your skill set and innovate
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