Data Science Director

Overview: 

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Director, Data Science. In this role, you will lead a team of data scientists in solving some of the most complex and high-impact challenges in the business. You will guide the development of advanced analytics, AI, and machine learning solutions while shaping strategy, influencing cross-functional decision-making, and building scalable processes that mature SageSure’s data capabilities. 

We are looking for a highly motivated, strategically minded, and innovative leader who thrives in both ambiguity and complexity—someone who can elevate team performance, collaborate across the organization, and set a vision for the future of Data Science at SageSure. 

What you’d be doing: 

• Partner with senior leaders across Product, Engineering, Program, and Operations to understand business needs and translate them into a cohesive Data Science strategy and roadmap. 
• Influence and align stakeholders by articulating clear priorities, trade-offs, and expected outcomes; ensure downstream teams have full context to execute effectively. 
• Foster a culture of accountability, collaboration, and continuous improvement across the team and cross-functional partners. 
• Lead, mentor, and develop a high-performing team of data scientists; provide coaching, career development, and structured feedback while ensuring clarity of expectations. 
• Build strong team health by promoting inclusion, psychological safety, and a values-driven culture. 
• Ensure the team structure, processes, and operating rhythms support long-term scalability and organizational needs. 
• Oversee the design, development, and deployment of machine learning models and advanced analytics solutions that drive business impact, improve operational efficiency, and strengthen decision-making. 
• Champion experimentation, innovation, and responsible use of AI; ensure solutions adhere to best practices in model governance, data ethics, and performance monitoring. 
• Translate complex technical concepts into clear, actionable insights for non-technical stakeholders, including senior executives. 
• Build and refine scalable processes, documentation, and standards that enhance quality, reproducibility, and onboarding efficiency. 
• Ensure responsible stewardship of data, models, and technical resources; make fiscally sound decisions aligned with departmental objectives and priorities. 
• Break down silos by promoting cross-functional problem-solving and encouraging teams to think beyond their lane to achieve shared goals.