Data Science / AI Lead

The DSAI Lead is responsible for driving business impact through the strategic delivery of Data Science and AI (DSAI) projects. This role leads a multidisciplinary team and works closely with Product Management, IT, Climate, Risk, GIS and Business teams to ensure the successful implementation of data-driven solutions. The incumbent ensures that the DSAI operating model functions effectively and evolves to meet organizational needs.

Key Responsibilities:

Project Leadership & Delivery Leads the end-to-end lifecycle of DSAI solutions, including design, planning, development, testing, deployment, and value realization. Oversees data collection, exploratory data analysis (EDA), model development, evaluation, and deployment. Collaborates with data leadership to track project progress and ensure alignment with business objectives. Cross-functional Collaboration Partners with Product Managers and the PMO to align project goals and execution. Coordinates with IT teams for infrastructure provisioning, deployment, and support. Works closely with Climate, Risk, GIS and Business teams to integrate domain expertise into DSAI solutions. Domain Expertise Applies

experience

in peril modelling for perils such as floods, inundation, cyclones, hailstorms, etc including supported perils. Ensures scientific accuracy and relevance in modelling approaches. Operational Excellence Maintains and enhances the DSAI operating model to improve efficiency and productivity. Recommends and implements best practices, tools, and frameworks for solution development. Team Management Manages the team’s skill matrix and develops a structured learning calendar. Oversees performance management processes including goal-setting, mid-year reviews, and annual evaluations. Fosters a culture of innovation, accountability, and continuous improvement.

Requirements

Qualifications

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Skills

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Experience:

Demonstrated

experience

in leading data science and AI teams. Strong foundation in statistical modelling, machine learning, and AI deployment.

Experience

in peril modelling, climate risk, insurance and geospatial analytics. Excellent stakeholder management and cross-functional collaboration skills. Proficiency with modern data science tools, Azure cloud platform, and deployment frameworks. Minimum 7-8 years in data science/AI roles, with at least 2-3 years in a lead position. Familiarity with agile project management and enterprise IT environments. Strong leadership, communication, and mentoring abilities.

Qualifications

/

Skills

/

Experience:

Demonstrated

experience

in leading data science and AI teams. Strong foundation in statistical modelling, machine learning, and AI deployment.

Experience

in peril modelling, climate risk, insurance and geospatial analytics. Excellent stakeholder management and cross-functional collaboration skills. Proficiency with modern data science tools, Azure cloud platform, and deployment frameworks. Minimum 7-8 years in data science/AI roles, with at least 2-3 years in a lead position. Familiarity with agile project management and enterprise IT environments. Strong leadership, communication, and mentoring abilities.