Lead Data Scientist - Property Catastrophe (CAT) Modeling & Geo-Analytics

About this role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Scientist - Property Catastrophe (CAT) Modeling & Geo-Analytics based in United States.
This role offers the opportunity to apply advanced data science and machine learning expertise to solve complex business challenges and drive measurable growth.


You will partner with business leaders across marketing, sales, and customer experience to uncover insights and create scalable analytical solutions.


The position combines technical leadership, predictive modeling, experimentation, and strategic thinking to improve customer acquisition, engagement, and retention.


You will design and deploy AI-driven solutions while helping teams make smarter, data-informed decisions.


As a senior technical contributor, you will influence data science practices, mentor junior team members, and promote innovation across the organization.


This role is ideal for a data science leader who enjoys solving ambiguous problems and translating complex analytics into meaningful business outcomes.


You will work in a collaborative environment where technology, analytics, and business strategy come together to create lasting impact.


Accountabilities

• Partner with Marketing, Sales, and Customer Experience leaders to identify business opportunities, define analytical strategies, and develop growth initiatives.
• Create advanced analyses, predictive models, and analytical frameworks to optimize customer acquisition, engagement, retention, and overall business performance.
• Develop and implement scalable machine learning solutions, including targeting models, customer segmentation, uplift modeling, and lifetime value prediction.
• Drive data-driven experimentation, measurement strategies, and optimization efforts to improve efficiency, customer outcomes, and return on investment.
• Translate complex data findings into ...