Key Responsibilities:

• Leading analytical conversation with business centred on “The art of the possible using data science”, exploring data from a modelling perspective, and performing initial exploratory data analysis to assess business value


• Working with information management specialists to identify and classify new feature sets, explore machine learning algorithms, and extract new feature sets


• Working in close partnership with analytics managers to size analytical opportunities and execute plans that ensure a positive commercial return


• Managing day-to-day relationships with offshore analytics teams


• Developing, implementing and maintaining analytical models to identify fraud, drive recoveries and renewals, drive profitable growth, and improve underwriting, pricing and claims performance


• Building analytical application designs and prototyping to test ideas and drive innovation in an agile fashion


• Working with analytics partners to build and operationalise models, quantifying and analysing model performance, and overseeing model refreshing requirements


• Managing analytical projects and coordinating activities with other shared services partners by prioritising relevant activities and providing subject matter expertise


• Assisting in the development of commercial propositions involving the use of analytics within insurance core functions through own analysis, prior experience, and research & development


• Implementing fit-for-purpose analytics tools and infrastructure that will be adopted by end users (e.g. claims handlers)


• Contributing to IT strategy


• Positively promoting the department, division and company as a whole, in order to maximise brand leverage and develop the team’s profile


• Actively undertaking personal development to ensure up-to-date skills and knowledge


• Acting as a point of reference to guide and advise junior members of the team to ensure sharing of knowledge and best practice


• Contributing to a positive environment by demonstrating cultural expectations and guiding leaders to reward performance, and valuing “can do” people, accountability, diversity and inclusion, flexibility, continuous improvement, collaboration, creativity and fun


• Adopting QBE values in personal work behaviours, decision-making, contributions and interpersonal interactions


• Managing own career development by soliciting feedback and valuing other perspectives

What does success look like?

• Degree qualified in econometrics, mathematics, statistics or related discipline


• Track record of implementing models that deliver significant sustained business impact


• Good understanding of Data Science domain, statistical and analytical model development and implementation


• Proficient in machine learning techniques and related disciplines


• Significant data management experience, gained from within the financial services sector, ideally within general insurance


• Good understanding of data modelling techniques, tools/language - Python preferred.


• Strong project management, collaboration and communication skills


• Ability to apply logic and reasoning to identify solutions to complex business problems and implement solutions


• Business and financial acumen


• Curiosity to learn and keep up with market trends and innovations


• Flexibility to adapt in a complex changing environment


• Ability to lead, manage and motivate a team, engage and influence stakeholders at all levels


• Strong written and verbal communication skills