Lead Data Scientist I, Lifetime Value

At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all.

We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love.

The Opportunity

We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry.

Join our Lifetime Value (LTV) team as a Lead Data Scientist I to improve how Root models customer value and uses it to inform decisions across the customer lifecycle. In this role, you’ll contribute to both predictive and scenario-based modeling to help forecast outcomes, evaluate business strategies, and support long-term planning.

You'll deepen Root's understanding of how key decisions in pricing, marketing, and customer experience influence lifetime value. Working closely with cross-functional partners, you'll build scalable tools and frameworks that support experimentation, risk assessment, and uncertainty quantification—empowering smarter, more consistent decision-making throughout the company.

Salary Range: $140,000 - $192,000 (Bonus and LTI Eligible)

Root is a “work where it works best” company, meaning we will support you working in whatever location that works best for you across the US.

How You Will Make an Impact

• Develop rigorous causal models that quantify how pricing, marketing, and product decisions impact profitability to influence strategic decisions across the company
• Introduce novel methods for extracting causal signals from complex, confounded data, and raise the organization’s standards for statistical rigor
• Build and operationalize scenario-based simulation tools that forecast how business interventions will play out in customer behavior, growth, and financial outcomes
• Identify new data and modeling techniques to improve model accuracy and customer segmentation
• Continuously monitor model performance, refine evaluation methods, and respond quickly to emerging trends
• Collaborate with cross-functional partners to align modeling priorities with business needs and produce actionable results

What You Will Need to Succeed

• Advanced degree in a quantitative discipline (PhD preferred) and 5+ years of applying advanced quantitative techniques to problems in industry
• Expertise in Python, SQL, and modern data science workflows (version control, cloud environments, etc.)
• Demonstrated success in building models that drive business impact—forecasting, simulation, or causal inference experience strongly preferred
• Excellent communication skills: conveys complex analyses and insights clearly to both technical and non-technical audiences
• Ability to consider problems from first principles, combining critical thinking with domain knowledge to navigate ambiguity
• Ownership mentality: takes the initiative to identify, champion, and execute on the highest impact work

As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.