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 / 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.