Senior Data Scientist

Brown & Brown Insurance

9d•$75,000 - $110,000

About The Position

Brown & Brown is seeking a Senior Data Scientist to join its Digital Innovation team. The role leads the company’s data science and advanced analytics capabilities to support informed decision-making, operational efficiency, and risk-aware growth. The Senior Data Scientist partners with business, technology, and risk stakeholders to design and deploy predictive analytics and modeling solutions that are explainable, responsible, and appropriate for a regulated insurance environment. The position provides technical leadership to data scientists and analysts, establishes clear priorities and performance standards, and communicates insights to non-technical leaders to support confident decision-making.

Requirements

Bachelor’s degree in Data Science, Engineering, or a related field.
15+ years of progressive experience in data, analytics, engineering, or related fields.
Proven success building and scaling enterprise data platforms and modern data architectures.
Deep expertise in data governance, data engineering, and analytics enablement, with strong familiarity with AI/ML concepts.
Ability to operate in a fast-paced, outcomes-driven environment with a strong bias for action.
Strong business acumen and a track record of enabling measurable business value through data.
Exceptional communication, leadership, and stakeholder-management skills.
Experience driving organizational change and building data-driven cultures.
Strong understanding of regulatory, ethical, and security considerations related to data and AI.

Nice To Haves

Experience in the insurance industry, including risk and regulatory considerations.
Master’s degree in Data Science, Engineering, or a related field.

Responsibilities

Lead the development and delivery of data science and advanced analytics solutions supporting underwriting insight, operational performance, and risk management.
Translate business problems into scalable analytical use cases aligned with regulatory and risk expectations.
Oversee the design, validation, deployment, and monitoring of predictive models with appropriate documentation and controls.
Partner with data governance and risk teams to ensure model explainability and compliance.
Provide technical leadership to a team of data scientists and analysts, setting clear priorities and performance standards.
Communicate insights clearly to non-technical leaders to support confident decision-making.