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.
