Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us.
Requirements
A degree in a highly quantitative field such as Computer Science, Mathematics, Statistics or equivalent, postgraduate studies preferred.
Demonstrated experience in a Data Scientist role, applying Data Science Methods to solve real-world business problems within a commercial setting.
Experience using data mining, statistical methods and machine-learning techniques.
Ability to navigate complexity and ambiguity to provide pragmatic commercial solutions which meet stakeholder expectations.
Excellent verbal and written communication skills, capable of communicating with audiences at all levels with clarity, impact and influence.
Good understanding of ML ops and strong Python programming skills.
Ability to plan and prioritise effectively, organise tasks and manage competing resources and demands.
Proven analytical and critical thinking capability to interpret a range of data, identify patterns, trends and links that inform judgements and solutions and report accordingly.
Demonstrated ability to build effective relationships internally and externally with stakeholders, intermediaries and service providers.
Highly developed 'first principles' problem-solving skills, combined with a curious and creative mind-set.
Highly developed consulting and influencing skills, demonstrating the ability to co-create strategy and valuable analytical solutions with key business stakeholders.
Demonstrated ability in innovative development practices, able to generate data science prototypes rapidly using relevant techniques.
Significant experience in data science and analytics, general insurance, and predictive modelling such as quote conversion, customer retention, with ML techniques, acquired in a complex, matrixed General Insurer.
Tech Stack
Python
Benefits
We at Allianz believe in a diverse and inclusive workforce and are proud to be an equal opportunity employer. We encourage you to bring your whole self to work, no matter where you are from, what you look like, who you love or what you believe in.