Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

Mercury Insurance

Lead Data Scientist developing scalable AI solutions at Mercury Insurance. Partnering with Marketing, Sales, and CX to drive growth strategies and data-driven decisions.

Posted 7/9/2026full-timeRemote • Alabama, Alaska, Arizona, Colorado, Connecticut, Florida, Hawaii, Idaho, Illinois, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Minnesota, Mississippi, Missouri, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming • 🇺🇸 United StatesSenior💰 $118,664 - $230,619 per yearWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Work directly with Marketing, Sales, and CX leaders to diagnose business challenges, define analytical roadmaps, and drive growth strategies.
Develop rigorous analyses, models, and frameworks to optimize customer acquisition, lifecycle engagement, and retention.
Build scalable machine learning solutions (e.g., targeting, segmentation, uplift modeling, LTV prediction) that improve growth efficiency and ROI.
Drive acquisition, retention, and monetization through data-driven experimentation and modeling.
Translate complex data insights into clear, actionable recommendations that influence decision-making at all levels of the organization.
Collaborate with engineering teams to productionize models and analytics pipelines with high reliability and performance.
Familiar with state of art AI solutions in Data Science domain and mentor Jr. data scientists.
Drive best practices in experimentation, measurement, and growth analytics across the company.

Requirements

What you’ll need

Minimum: Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related technical field
7+ years of experience in data science, machine learning, or growth analytics, with a track record of delivering business impact.
5 years of experience in data mining and data/statistical analysis.
5 years experience with SQL and statistical software packages (Python, R, SAS) required.
5 years experience working as a data scientist or similar role, with proven track record in data processing, predictive modeling, and machine learning techniques.
1 year experience in P&C insurance.
1 year experience leading projects in group settings and mentoring peers/interns.
Expert-level SQL and Python, and experience working in modern data and ML ecosystems.
Experiences in growth-focused data science (e.g., paid marketing optimization, attribution, funnel diagnostics, experimentation, user segmentation).
Design and lead complex A/B/n testing frameworks, including multi-armed bandits and causal inference models to measure impact in ambiguous environments.
Hands-on experience building and deploying production ML models.
Experience in fine-tuning Generative AI (LLMs) for domain-specific applications is a plus.

Benefits

Comp & perks

Competitive compensation
Flexibility to work from anywhere in the United States for most positions
Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)
Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)
Medical, dental, vision, life, and pet insurance
401 (k) retirement savings plan with company match
Engaging work environment
Promotional opportunities
Education assistance
Professional and personal development opportunities
Company recognition program
Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data MiningStatistical AnalysisPredictive ModelingA/B TestingGenerative AI Fine-TuningData ProcessingModel DeploymentExperimentationUser SegmentationCausal Inference

Soft Skills

CollaborationMentoringCommunicationProblem-SolvingLeadership