The Director of Modeling & Insights will lead the development, validation, and scaling of advanced
analytic models, both predictive and prescriptive, that generate meaningful business insights across key functions, including claims, underwriting, distribution, and pricing. This role will drive modeling innovation, ensure strong governance practices, and promote analytic thought leadership across the organization.
Responsibilities:
Provide hands-on technical leadership throughout the modeling lifecycle, including problem
framing, feature engineering, model selection, validation, explainability, monitoring, and retraining.
Produce actionable, high-value insights that demonstrate measurable business impact;
collaborate with business partners to pilot and scale solutions.
Own and oversee the model validation process for advanced analytics, ensuring rigor and
compliance through both internal and independent validation.
Lead the innovation agenda by identifying and implementing new use cases for machine
learning and AI, as well as A/B testing frameworks, uplift modeling, and automation
opportunities.
Mentor and develop data scientists, modelers, and actuarial modelers; establish best practices,
reusable components, and consistent methodologies across analytics teams.
Ensure transparency, interpretability, and regulatory alignment of models to build trust among
business stakeholders and regulators.
Required Skills and Abilities:
Strong expertise in machine learning, predictive modeling, and advanced analytics.
Deep understanding of model lifecycle management, validation, and governance processes.
Ability to translate complex technical findings into clear, actionable business insights.
Proven leadership in cross-functional collaboration and mentorship within data and analytics
teams.
Strong communication and storytelling skills to influence business and executive stakeholders.
Commitment to transparency, explainability, and compliance in model design and deployment.
Education and Experience:
Bachelor’s degree in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science,
or a related quantitative field.
FCAS (Fellow of the Casualty Actuarial Society) or ACAS (Associate of the Casualty Actuarial
Society) preferred.
10+ years of experience in data science, analytics, or actuarial modeling roles, with progressive
leadership responsibilities.
Demonstrated success in developing and deploying advanced analytic models that drive
measurable business outcomes.
Experience in insurance, financial services, or a similar highly regulated industry strongly
preferred.
Physical Requirements:
Prolonged periods of sitting at a desk and working on a computer, including video conferencing.
