Senior AI / ML Engineer I

Purpose of Role
The Data Scientist is a crucial role within our insurance company, responsible for leveraging their expertise in data science and analytics to identify and pursue new business opportunities, renewals, and/or claims optimization.

This position requires a strong background in data analysis, statistical modelling, and machine learning algorithms.
This role is responsible for conducting robust quantitative and statistical analysis of our insurance product offerings and portfolio.

The role involves leveraging complex data sets to identify trends, patterns and insights that serve to improve business development, design, and evaluation of new products, and evaluate external data.

In this pivotal role, the Data Scientist will collaborate closely with various stakeholders including underwriting, actuarial, risk management and the executive team, assisting in driving evidence-based decisions, promoting profitable business growth, renewals, and/or claims efficiency.

Key Accountabilities & Responsibilities

• Analyse large datasets using advanced statistical methods to uncover trends, patterns, gaps, and insights that can be leveraged for business growth, renewals, and/or claims optimization.
• Collaborate with cross-functional teams to understand business objectives and identify areas where data-driven solutions can drive revenue growth, renewals, and/or claims efficiency.
• Design and implement experiments to test hypotheses and analyse the impact of various factors on business performance, renewals, and claims outcomes.
• Develop machine learning models to automate decision-making processes and improve operational efficiency.
• Create data visualizations and communicate findings to stakeholders in a clear and concise manner, providing insights for business decision-making.
• Stay up to date with the latest advancements in data science and actively seek opportunities to apply new techniques and tools to enhance business opportunities.
• Work closely with data engineering teams to optimize data storage, retrieval, and processing, ensuring efficient handling of datasets.
• Work closely with machine learning engineers to facilitate the seamless deployment of models.