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Strong employer brand, mid-level ML role, and popular data science skillset increase candidate competition.
Core ML skills are transferable but insurance and Agentic/Generative AI requirements add industry specificity.
Multiple mandatory years and specialized AI plus industry skills create strict shortlisting filters.
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Apply advanced data science and machine learning techniques to develop predictive models addressing commercial insurance business problems such as quote conversion and customer retention.
Build data science prototypes rapidly using innovative methods for stakeholder-driven analytical solutions within a complex, matrixed general insurance environment.
Collaborate with diverse internal and external stakeholders to co-create strategies and pragmatic, commercially viable AI-driven solutions that navigate organizational complexity.
5+ years of professional experience in Data Science.
1+ year experience in Agentic AI Development and 2+ years experience in Generative AI.
Degree in a quantitative field such as Computer Science, Mathematics, or Statistics; postgraduate studies preferred.
Strong skills in Python programming, ML Ops understanding, and experience with data mining, statistical and machine learning techniques, specifically within general insurance predictive modelling.
Experienced in complex, matrixed general insurance environments with business problem-solving using data science and predictive analytics.
Demonstrates ability to effectively influence and consult with senior business stakeholders to co-create analytical strategies and solutions.
Capable of rapidly prototyping data science models and navigating ambiguity to deliver pragmatic, stakeholder-aligned AI solutions.