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Director Data Science

Job in Mountain View, Santa Clara County, California, 94039, USA
Listing for: SageSure Insurance Managers LLC
Full Time position
Listed on 2026-10-09
Job specializations:
  • IT/Tech
    Data Science Manager, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 210000 - 320000 USD Yearly USD 210000.00 320000.00 YEAR
Job Description & How to Apply Below

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. Sage Sure, 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 Sage Sure’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 Sage Sure.

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.
We’re looking for someone who has:
  • Bachelor’s or Master’s degree in a quantitative field (Data Science, Computer Science, Statistics, Mathematics, etc.).
  • 3+ years of leadership experience managing data scientists or analytics teams in a fast-paced environment.
  • Deep expertise in Python, SQL, and modern data science/ML tooling (Pandas, Num Py, Tensor Flow, etc.).
  • Strong understanding of AWS or comparable cloud architecture.
  • Demonstrated success delivering machine learning solutions that drive measurable business outcomes.
  • Proven ability to think strategically, manage complex initiatives, and prioritize effectively across competing demands.
  • Exceptional communication skills, with the ability to influence senior executives and guide teams through ambiguity.
Highly preferred candidates also have:
  • Experience in P&C insurance or another highly regulated, data-intensive industry.
  • Exposure to large-scale, real-time data pipelines and MLOps practices.
  • Experience building cross-functional operating models, processes, or governance frameworks.
  • Experience leading through organizational change and…
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