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

About the role

This position 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.

Responsibilities

• 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 clear business recommendations and communicate insights effectively to technical and non-technical stakeholders.
• Collaborate with engineering teams to deploy machine learning models and analytics solutions into reliable, production-ready systems.
• Stay current with emerging AI and data science technologies and apply innovative approaches to solve business challenges.
• Establish best practices for experimentation, analytics, modeling, and measurement across the organization.
• Provide technical leadership and mentorship to junior data scientists, supporting skill development and high-quality analytical work.
• Lead projects in complex, ambiguous environments where data-driven solutions require strategic thinking and creative problem-solving.

Requirements

• Bachelor’s degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or a related technical field, or equivalent professional experience.
• Master’s degree or Ph.D. in a related discipline is preferred.
• 7+ years of experience in data science, machine learning, analytics, or related fields with a demonstrated ability to deliver measurable business impact.
• Strong experience in data mining, statistical analysis, predictive modeling, and machine learning techniques.
• Expert-level proficiency in SQL and Python, with experience working in modern data and machine learning ecosystems.
• Experience designing and deploying production machine learning models and scalable analytics solutions.
• Strong background in growth-focused data science, including customer acquisition optimization, attribution analysis, funnel diagnostics, experimentation, and segmentation.
• Experience designing and leading advanced experimentation frameworks, including A/B testing, multi-armed bandits, and causal inference models.
• Experience applying AI techniques, including generative AI or large language model solutions, is a plus.
• Strong business and product intuition with the ability to collaborate effectively with senior stakeholders.
• Excellent communication and storytelling skills, with the ability to simplify complex technical concepts for diverse audiences.
• Able to operate effectively in undefined problem spaces and create solutions where clear answers may not initially exist.
• Experience in consumer, fintech, SaaS, insurance, or marketplace environments is preferred.
• Experience mentoring peers, interns, or junior team members is preferred.

Benefits

Competitive annual salary range of approximately $97,089 - $230,619, depending on location, experience, skills, and qualifications.
Flexible work options, including the ability to work remotely from anywhere in the United States for eligible positions.
Comprehensive benefits package including medical, dental, vision, life, and pet insurance.
401(k) retirement savings plan with company matching.
Paid time off, including vacation time, sick leave, company holidays, and volunteer hours.
Incentive bonus opportunities, including performance-based and referral programs.
Professional development opportunities, education assistance, and career growth support.
Health and wellbeing resources, including mental wellness programs and family support services.
Recognition programs celebrating employee contributions and achievements.
Collaborative and inclusive workplace culture focused on innovation, growth, and teamwork.