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

Join an amazing team that is consistently recognized for our achievements and culture, including our most recent Forbes award of being one of America's Best Midsize Employers for 2026!

Position Summary:

We are looking for an experienced Lead Data Scientist to join our Growth Data Science team at Mercury Insurance. In this role, you will partner closely with our Marketing, Sales, and Customer Experience organizations to identify growth opportunities, optimize acquisition and engagement strategies, and deliver scalable, data-driven solutions. You will act as a thought leader—bring deep technical expertise, strong business intuition, and the ability to drive measurable business value through automated, domain-specific AI solutions.

An in-person interview may be required during the hiring process

State specific pay scales for this role are as follows:

$118,664 to $230,619 (NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$107,876 to $209,653 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$97,089 to $188,688 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)

In CA: Typical hiring range is $157,177.35  to $218,301.88 

The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.

Essential Job Functions:

• 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.

Education:

Minimum:

• Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related technical field Or equivalent combination of education and/or experience

Preferred:

• MS/Ph.D. is preferred.

Experience:

Minimum:

• 7+ years of experience in data science, machine learning, or growth analytics, with a track record of delivering business impact.

Preferred: 

• 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

Knowledge and Skills:

• 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.
• Solid communication skills—able to simplify complex concepts for non-technical partners and good storytelling skills. 
• Ability to operate in "zero-to-one" problem spaces where clear ground truths may not exist.
• Strong product and business intuition; comfortable partnering with senior-level stakeholders.
• Experience in a consumer, fintech, SaaS, or marketplace environment is a plus.

Why choose a career at Mercury?

At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it.

Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life.

We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals.

Learn more about us here: https://www.mercuryinsurance.com/about/careers

We offer many great benefits, including:

• 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

Mercury Insurance is an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law.