Experience of working in a regulatory oversight role (such as compliance, risk, controls, audit, assurance, privacy) in the retail or investment banking sector with a focus on consumer and client conduct risk.
Experience with, or managing a programming team, using computer languages (e.g. R, Python, SAS or similar) to manipulate data and visualise insights from large and varied data sources (e.g. R, Python, Tableau).
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, neural networks, text analytics / Natural Language Processing) and their real-world advantages/drawbacks.
Experience of designing robust data governance and managing sustainable, scalable data infrastructures with consideration to security, privacy and risk.
Experience of data analysis and proven ability for pragmatic problem solving to reach sound judgements with incomplete information in an agile, iterative environment.
Proven ability to explain data analysis, insights and capabilities to audiences with differing technical backgrounds.
Experience of leading a multiple location team for the development of solutions addressing business needs with experience of leading change and enhancement programmes as well as embedding new cultural ways of working.
Desirable skills/Preferred Qualifications:
Relevant professional qualification(s) or postgraduate degree
Experience with new technologies in delivering banking services and digital customer / client experience.
Ability to provide strong people leadership, performance management and talent development.
Experience of enterprise risk management and working across silos, departments and working cultures.
Knowledge of critical regulation and guidance covering conduct risk in the context of personal data and technologies eg GDPR (EU), Regulation B (US), CONC (UK), etc.